xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

94553888d69c9264fdada0c0363badbaf30c59ca

304

py

Python

textattack/metrics/attack_metrics/__init__.py

srujanjoshi/TextAttack

b86d0f840b6f13b1eb8d0f17b3fceeeca62b08ed

[ "MIT" ]

null

textattack/metrics/attack_metrics/__init__.py

srujanjoshi/TextAttack

b86d0f840b6f13b1eb8d0f17b3fceeeca62b08ed

[ "MIT" ]

null

textattack/metrics/attack_metrics/__init__.py

srujanjoshi/TextAttack

b86d0f840b6f13b1eb8d0f17b3fceeeca62b08ed

[ "MIT" ]

1

2022-03-06T22:41:03.000Z

""" attack_metrics package: --------------------------------------------------------------------- TextAttack provide users common metrics on attacks' quality. """ from .attack_queries import AttackQueries from .attack_success_rate import AttackSuccessRate from .words_perturbed import WordsPerturbed

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1

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1

0

4

945a573532de5f16c4b4354385719ebffdfdc80b

242

py

Python

UltimateTicTacToe/Bot.py

m3rik/nn

96d630cbb9894957d17ca8291900ff3802a30637

[ "Apache-2.0" ]

null

UltimateTicTacToe/Bot.py

m3rik/nn

96d630cbb9894957d17ca8291900ff3802a30637

[ "Apache-2.0" ]

null

UltimateTicTacToe/Bot.py

m3rik/nn

96d630cbb9894957d17ca8291900ff3802a30637

[ "Apache-2.0" ]

null

class Bot: ''' state - state of the game returns a move ''' def move(self, state, symbol): raise NotImplementedError('Abstractaaa') def get_name(self): raise NotImplementedError('Abstractaaa')

22

48

0.603306

25

242

5.8

0.68

0.331034

0.482759

0

0.297521

242

10

49

24.2

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null

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4

9465d06fb72f797af7607ca889bd481b18264799

91

py

Python

working-library/background/LoginAPI/apps.py

FredCof/Fresh-supermarket-Online

25c1cb28f5b5dc1f85e53ee7de5b055de438c491

[ "Apache-2.0" ]

2

2021-03-12T16:35:27.000Z

2021-03-12T16:35:34.000Z

working-library/background/LoginAPI/apps.py

FredCof/Fresh-supermarket-Online

25c1cb28f5b5dc1f85e53ee7de5b055de438c491

[ "Apache-2.0" ]

4

2021-03-19T13:16:08.000Z

2021-06-09T19:26:37.000Z

working-library/background/LoginAPI/apps.py

FredCof/Fresh-supermarket-Online

25c1cb28f5b5dc1f85e53ee7de5b055de438c491

[ "Apache-2.0" ]

null

from django.apps import AppConfig class LoginapiConfig(AppConfig): name = 'LoginAPI'

15.166667

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91

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947828473b636b1609d039fe780a63c63434f7d9

213

py

Python

oozappa/_structure/_environment/fabfile/__init__.py

tsuyukimakoto/oozappa

51a8fad38a1ad34514853d0223619c6ec667c213

[ "MIT" ]

8

2015-05-10T21:59:30.000Z

2017-11-24T03:49:12.000Z

oozappa/_structure/_environment/fabfile/__init__.py

frkwy/oozappa

92a631d26573ac53b3f2f852ab391a22561189e1

[ "MIT" ]

12

2015-01-25T13:43:35.000Z

2018-11-01T17:37:26.000Z

oozappa/_structure/_environment/fabfile/__init__.py

frkwy/oozappa

92a631d26573ac53b3f2f852ab391a22561189e1

[ "MIT" ]

4

2015-10-03T08:43:11.000Z

2017-12-15T08:57:23.000Z

# -*- coding:utf8 -*- from fabric.api import task, local, run, sudo, env from oozappa.config import get_config, procure_common_functions _settings = get_config() procure_common_functions() # your own task below

23.666667

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0.280255

0.394904

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213

8

64

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null

0

1

0

4

947e3f8031704f990091dfcbbbcfe194d5d16baa

204

py

Python

build/lib/mezzanine_smartling/urls.py

Appdynamics/mezzanine-smartling

76ca1dd929ff79e6c766eb46237edc6ab6d38a46

[ "Apache-2.0" ]

3

2015-10-09T01:12:27.000Z

2015-10-10T09:41:56.000Z

build/lib/mezzanine_smartling/urls.py

Appdynamics/mezzanine-smartling

76ca1dd929ff79e6c766eb46237edc6ab6d38a46

[ "Apache-2.0" ]

null

build/lib/mezzanine_smartling/urls.py

Appdynamics/mezzanine-smartling

76ca1dd929ff79e6c766eb46237edc6ab6d38a46

[ "Apache-2.0" ]

2

2018-10-14T10:32:00.000Z

2019-08-22T06:07:28.000Z

from django.conf.urls import include, url from django.contrib import admin urlpatterns = [ url(r'^smartling_callback/$', 'mezzanine_smartling.views.smartling_callback', name='smartling_callback'), ]

29.142857

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0.779412

25

204

6.2

0.64

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0

0.102941

204

6

110

34

0.846995

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0.406863

0.318627

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1

0

1

0

null

0

1

0

4

846c3ddd8708d943b4bedd8aee1bf379f7ad60ea

5,805

py

Python

ee569/hw5/model.py

chenying-wang/usc-ee-coursework-public

5bc94c2350bcebf1036fb058fe7dc4f7e31e1de1

[ "MIT" ]

1

2021-03-24T10:46:20.000Z

ee569/hw5/model.py

chenying-wang/usc-ee-coursework-public

5bc94c2350bcebf1036fb058fe7dc4f7e31e1de1

[ "MIT" ]

null

ee569/hw5/model.py

chenying-wang/usc-ee-coursework-public

5bc94c2350bcebf1036fb058fe7dc4f7e31e1de1

[ "MIT" ]

1

2021-03-25T09:18:45.000Z

# Name: Chenying Wang # Email: chenying.wang@usc.edu # USC ID: ****-****-** # Date: Friday, April 3, 2020 import tensorflow as tf import argparse import config class BaseModel: def __init__(self, inputs_shape, lr_rate = config.SGD_LEARNING_RATE, lr_decay_steps = config.SGD_LEARNING_RATE_DECAY_STEPS, \ lr_decay_rate = config.SGD_LEARNING_RATE_DECAY_RATE, name = 'model', **kwargs): self._build_model(inputs_shape, lr_rate, lr_decay_steps, lr_decay_rate, name) def fit(self, *args, **kwargs): self._model.fit(*args, **kwargs) def evaluate(self, *args, **kwargs): self._model.evaluate(*args, **kwargs) def load_weights(self, *args, **kwargs): self._model.load_weights(*args, **kwargs) def _build_model(self, inputs_shape, lr_rate, lr_decay_steps, lr_decay_rate, name): inputs = tf.keras.Input(inputs_shape) outputs = self.call(inputs) self._model = tf.keras.Model(inputs = inputs, outputs = outputs, name = name) self._model.summary() if lr_decay_steps <= 0: optimizer = tf.keras.optimizers.SGD(learning_rate = lr_rate, momentum = 0.9) else: lr_schedule = tf.keras.optimizers.schedules.ExponentialDecay(lr_rate, \ decay_steps = lr_decay_steps * config.TRAIN_SIZE // config.BATCH_SIZE, \ decay_rate = lr_decay_rate, staircase = True) optimizer = tf.keras.optimizers.SGD(learning_rate = lr_schedule, momentum = 0.9) self._model.compile(optimizer = optimizer, \ loss = tf.keras.losses.SparseCategoricalCrossentropy(), \ metrics = ['accuracy']) class LeNet5Model(BaseModel): def __init__(self, inputs_shape, lr_rate = config.SGD_LEARNING_RATE, lr_decay_steps = config.SGD_LEARNING_RATE_DECAY_STEPS, \ lr_decay_rate = config.SGD_LEARNING_RATE_DECAY_RATE, name = 'model', **kwargs): self.conv_1 = tf.keras.layers.Conv2D(6, (5, 5), padding = 'valid', \ input_shape = (config.CHANNEL, config.HEIGHT, config.WIDTH), \ data_format = 'channels_first', name = 'Conv_1') self.pool_1 = tf.keras.layers.MaxPool2D((2, 2), data_format = 'channels_first', name = 'Pool_1') self.conv_2 = tf.keras.layers.Conv2D(16, (5, 5), padding = 'valid', \ data_format = 'channels_first', name = 'Conv_2') self.pool_2 = tf.keras.layers.MaxPool2D((2, 2), data_format = 'channels_first', name = 'Pool_2') self.flatten = tf.keras.layers.Flatten(name = 'Flatten') self.fc_1 = tf.keras.layers.Dense(120, activation = tf.nn.swish, name = 'Fc_1') self.dropout_1 = tf.keras.layers.Dropout(config.DROPOUT_RATE, name = 'Dropout_1') self.fc_2 = tf.keras.layers.Dense(84, activation = tf.nn.swish, name = 'Fc_2') self.dropout_2 = tf.keras.layers.Dropout(config.DROPOUT_RATE, name = 'Dropout_2') self.fc_3 = tf.keras.layers.Dense(10, activation = tf.nn.softmax, name = 'Prediction') super(LeNet5Model, self).__init__(inputs_shape, lr_rate, lr_decay_steps, lr_decay_rate, name, **kwargs) def call(self, inputs, training = None): x = self.conv_1(inputs) x = tf.nn.relu(x) x = self.pool_1(x) x = self.conv_2(x) x = tf.nn.relu(x) x = self.pool_2(x) x = self.flatten(x) x = self.fc_1(x) x = self.fc_2(x) prediction = self.fc_3(x) return prediction class ModifiedLeNet5Model(BaseModel): def __init__(self, inputs_shape, lr_rate = config.SGD_LEARNING_RATE, lr_decay_steps = config.SGD_LEARNING_RATE_DECAY_STEPS, \ lr_decay_rate = config.SGD_LEARNING_RATE_DECAY_RATE, name = 'model', **kwargs): self.conv_1 = tf.keras.layers.Conv2D(32, (5, 5), padding = 'valid', \ kernel_regularizer = tf.keras.regularizers.l2(config.WEIGHT_DECAY), \ input_shape = (config.CHANNEL, config.HEIGHT, config.WIDTH), \ data_format = 'channels_first', name = 'Conv_1') self.bn_1 = tf.keras.layers.BatchNormalization(axis = 1, name = 'BN_1') self.pool_1 = tf.keras.layers.MaxPool2D((2, 2), data_format = 'channels_first', name = 'Pool_1') self.conv_2 = tf.keras.layers.Conv2D(64, (5, 5), padding = 'valid', \ kernel_regularizer = tf.keras.regularizers.l2(config.WEIGHT_DECAY), \ data_format = 'channels_first', name = 'Conv_2') self.bn_2 = tf.keras.layers.BatchNormalization(axis = 1, name = 'BN_2') self.pool_2 = tf.keras.layers.MaxPool2D((2, 2), data_format = 'channels_first', name = 'Pool_2') self.flatten = tf.keras.layers.Flatten(name = 'Flatten') self.fc_1 = tf.keras.layers.Dense(200, activation = tf.nn.swish, name = 'Fc_1') self.dropout_1 = tf.keras.layers.Dropout(config.DROPOUT_RATE, name = 'Dropout_1') self.fc_2 = tf.keras.layers.Dense(100, activation = tf.nn.swish, name = 'Fc_2') self.dropout_2 = tf.keras.layers.Dropout(config.DROPOUT_RATE, name = 'Dropout_2') self.fc_3 = tf.keras.layers.Dense(10, activation = tf.nn.softmax, name = 'Prediction') super(ModifiedLeNet5Model, self).__init__(inputs_shape, lr_rate, lr_decay_steps, lr_decay_rate, name, **kwargs) def call(self, inputs, training = None): x = self.conv_1(inputs) x = self.bn_1(x, training = training) x = tf.nn.swish(x) x = self.pool_1(x) x = self.conv_2(x) x = self.bn_2(x, training = training) x = tf.nn.swish(x) x = self.pool_2(x) x = self.flatten(x) x = self.fc_1(x) x = self.dropout_1(x, training = training) x = self.fc_2(x) x = self.dropout_2(x, training = training) prediction = self.fc_3(x) return prediction

50.043103

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809

5,805

4.349815

0.143387

0.059676

0.081273

0.053708

0.777778

0.741972

0.722648

0.650753

0

0.026655

0.224462

5,805

115

130

50.478261

0.754998

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false

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null

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1

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1

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null

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4

84726d6d0823305456f2e6b568610386b66386bb

157

py

Python

turf/invariant/__init__.py

malroc/pyturf

c89b6ea7094bd5ca26cf589d9dcd15bd819d82e9

[ "MIT" ]

11

2020-08-26T11:04:55.000Z

2022-01-26T14:53:10.000Z

turf/invariant/__init__.py

malroc/pyturf

c89b6ea7094bd5ca26cf589d9dcd15bd819d82e9

[ "MIT" ]

36

2020-04-09T16:49:05.000Z

2020-06-01T14:39:37.000Z

turf/invariant/__init__.py

malroc/pyturf

c89b6ea7094bd5ca26cf589d9dcd15bd819d82e9

[ "MIT" ]

5

2020-07-30T23:37:35.000Z

2021-08-24T08:10:28.000Z

from turf.invariant._invariant import ( get_coords_from_features, get_coords_from_geometry, get_geometry_from_features, get_geometry_type, )

22.428571

39

0.789809

20

157

5.6

0.45

0.160714

0.232143

0

0.159236

157

6

40

26.166667

0.848485

0

1

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true

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1

0

null

0

1

0

4

84cc4726f31db3c5dc0daf118ad72e6245b1f377

226

py

Python

usersmanagement/apps.py

Open-CMMS/openCMMS_backend

56511ebac83a5dc1fb8768a98bc675e88530a447

[ "BSD-3-Clause" ]

3

2021-03-08T19:14:38.000Z

2022-02-01T17:57:31.000Z

usersmanagement/apps.py

Open-CMMS/openCMMS_backend

56511ebac83a5dc1fb8768a98bc675e88530a447

[ "BSD-3-Clause" ]

null

usersmanagement/apps.py

Open-CMMS/openCMMS_backend

56511ebac83a5dc1fb8768a98bc675e88530a447

[ "BSD-3-Clause" ]

null

"""This file is to register usermanagement as a django app.""" from django.apps import AppConfig class UsersmanagementConfig(AppConfig): """This is the declaration of usermanagement app.""" name = 'usersmanagement'

25.111111

62

0.743363

27

226

6.222222

0.777778

0

0.163717

226

8

63

28.25

0.888889

0.455752

0

0.133929

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false

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0.333333

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0

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0

null

0

1

0

1

0

4

84daace86eeabe1ca23f2b46ff081b8bf2a65fe7

226

py

Python

test.py

amirrr/django-legislation-polling

a833d4bb535ffeffadbc2ad1ef9bc6bcedb15703

[ "MIT" ]

null

test.py

amirrr/django-legislation-polling

a833d4bb535ffeffadbc2ad1ef9bc6bcedb15703

[ "MIT" ]

null

test.py

amirrr/django-legislation-polling

a833d4bb535ffeffadbc2ad1ef9bc6bcedb15703

[ "MIT" ]

null

import os from random import randint def generate_verification_code(): n = 6 return ''.join(["{}".format(randint(0, 9)) for num in range(0, n)]) if __name__ == "__main__": print(generate_verification_code())

16.142857

71

0.668142

31

226

4.483871

0.774194

0.28777

0.345324

0

0.021739

0.185841

226

14

72

16.142857

0.733696

0

1

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0.044053

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0.142857

false

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0.142857

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null

1

0

1

0

null

0

1

0

4

84fe552ef6ab8a2e3de385d96a5875aebfb4a2fb

773

py

Python

relationship/serializers.py

Chren/FakeWechatServer

d6a94302ee242d01f74b59b17528e77d397e6e92

[ "MIT" ]

4

2016-11-15T16:42:51.000Z

2018-10-20T06:14:22.000Z

relationship/serializers.py

Chren/FakeWechatServer

d6a94302ee242d01f74b59b17528e77d397e6e92

[ "MIT" ]

null

relationship/serializers.py

Chren/FakeWechatServer

d6a94302ee242d01f74b59b17528e77d397e6e92

[ "MIT" ]

2

2016-12-05T10:04:48.000Z

2018-11-06T14:15:27.000Z

from rest_framework import serializers from relationship.models import IMUser, FriendShip from django.contrib.auth.models import User from rest_framework.fields import Field class IMUserSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = IMUser fields = ('userid', 'phone', 'name', 'photo', 'bgimg') class LoginUserSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = IMUser fields = ('userid', 'phone', 'name', 'photo', 'bgimg', 'token', 'rctoken') class ResponseSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = IMUser fields = ('userid', 'phone', 'name', 'photo', 'bgimg', 'token', 'rctoken')

35.136364

66

0.655886

70

773

7.214286

0.414286

0.219802

0.249505

0.273267

0.570297

0

0.231565

773

22

67

35.136364

0.850168

0

0.578947

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false

0

0.210526

0

0.526316

0

null

1

0

null

0

1

0

4

ca0d0c7baed43d68b540d99be74bffd5943fcf93

899

py

Python

api/serializers.py

crypticleopard/IIPEDIA

33717ccd2ff0f809dcb1953880769f423f64474c

[ "MIT" ]

1

2021-05-01T19:20:32.000Z

api/serializers.py

crypticleopard/IIPEDIA

33717ccd2ff0f809dcb1953880769f423f64474c

[ "MIT" ]

null

api/serializers.py

crypticleopard/IIPEDIA

33717ccd2ff0f809dcb1953880769f423f64474c

[ "MIT" ]

null

from rest_framework import serializers from .models import Book,Review,Community from django.contrib.auth.models import User class BookSerializer(serializers.ModelSerializer): class Meta: model=Book fields=('__all__') class CreateReviewSerializer(serializers.ModelSerializer): class Meta: model=Review fields=['main'] class CreateUserSerializer(serializers.ModelSerializer): class Meta: model=User fields=('username','password','email','first_name','last_name') class GetReviewSerializer(serializers.ModelSerializer): class Meta: model=Review fields=('__all__') class GetCommunitySerializer(serializers.ModelSerializer): class Meta: model=Community fields=('__all__') class CreateCommunitySerializer(serializers.ModelSerializer): class Meta: model=Community fields=['main']

27.242424

71

0.714127

84

899

7.464286

0.380952

0.248804

0.296651

0.334928

0.4689

0.341308

0

0.192436

899

33

72

27.242424

0.863636

0

0.555556

0

0.076667

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1

0

false

0.037037

0.111111

0

0.555556

0

null

1

0

null

0

1

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4

ca1033f1e9db5a5cd3212551dbe84e331887865e

21

py

Python

models/unet/EfficientNet_PyTorch/tf_to_pytorch/convert_tf_to_pt/original_tf/__init__.py

harsimarsingh/fastmrimine

77c79a4ce83f63537eb775fa1eb40feb699338ef

[ "MIT" ]

null

models/unet/EfficientNet_PyTorch/tf_to_pytorch/convert_tf_to_pt/original_tf/__init__.py

harsimarsingh/fastmrimine

77c79a4ce83f63537eb775fa1eb40feb699338ef

[ "MIT" ]

null

models/unet/EfficientNet_PyTorch/tf_to_pytorch/convert_tf_to_pt/original_tf/__init__.py

harsimarsingh/fastmrimine

77c79a4ce83f63537eb775fa1eb40feb699338ef

[ "MIT" ]

null

""" dummy comment """

21

0.571429

2

21

6

1

0

0.142857

21

1

21

0.666667

0.619048

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

ca10989707ee0ad9838a9b59928a0d604e96d599

210

py

Python

pitanja/views.py

denza/django-playground

a2eea580f4322973c51a0ea816b59513cd558b6c

[ "MIT" ]

1

2021-08-14T13:47:01.000Z

pitanja/views.py

denza/django-playground

a2eea580f4322973c51a0ea816b59513cd558b6c

[ "MIT" ]

null

pitanja/views.py

denza/django-playground

a2eea580f4322973c51a0ea816b59513cd558b6c

[ "MIT" ]

null

from django.shortcuts import render from .models import Osoba def poosobama(request): svao = Osoba.objects.all() return render(request, "pitanja/index.html", {'svao' : svao}) # Create your views here.

26.25

65

0.72381

28

210

5.428571

0.75

0

0.157143

210

7

66

30

0.858757

0.109524

0

0.118919

0

1

0.2

false

0

0.4

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0.8

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null

0

1

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null

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ca223d5a1fb6bd31c31c21778e08ed2f82f8434a

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py

Python

samples/sample_tap_countries/__init__.py

meltano/sdk

83dde4fe922f9f91bd3c57277849a2a2daa8f09a

[ "Apache-2.0" ]

13

2021-06-21T17:30:32.000Z

2021-12-06T18:45:34.000Z

samples/sample_tap_countries/__init__.py

meltano/sdk

83dde4fe922f9f91bd3c57277849a2a2daa8f09a

[ "Apache-2.0" ]

null

samples/sample_tap_countries/__init__.py

meltano/sdk

83dde4fe922f9f91bd3c57277849a2a2daa8f09a

[ "Apache-2.0" ]

null

"""Countries API Sample."""

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ca3ebc3ca74aba2e3008523848d23c4e2047c22c

219

py

Python

src/ui/components/__init__.py

Amin-egn/Recipient

51e98ef9e679b3f32db7ab2eb07f0a905f0dac24

[ "Apache-2.0" ]

null

src/ui/components/__init__.py

Amin-egn/Recipient

51e98ef9e679b3f32db7ab2eb07f0a905f0dac24

[ "Apache-2.0" ]

null

src/ui/components/__init__.py

Amin-egn/Recipient

51e98ef9e679b3f32db7ab2eb07f0a905f0dac24

[ "Apache-2.0" ]

null

from .base_widget import BaseWidget from .base_dialog import BaseDialog from .table import Table from .message import Message from .confirm import Confirm from .progress import Progress from .table_list import TableList

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ca40afa4d6bc3235c2086ba1bb9afb63b3dc6090

250

py

Python

api/serializers/subscribers.py

lucasmgana/Pharmacy-Light-weight

9d6efe714d60b3a04f78f174e1e6c2a2ab98bd9a

[ "MIT" ]

192

2020-08-14T22:17:34.000Z

2022-03-29T05:56:26.000Z

api/serializers/subscribers.py

lucasmgana/Pharmacy-Light-weight

9d6efe714d60b3a04f78f174e1e6c2a2ab98bd9a

[ "MIT" ]

9

2021-03-30T14:29:00.000Z

2022-02-27T11:06:35.000Z

api/serializers/subscribers.py

lucasmgana/Pharmacy-Light-weight

9d6efe714d60b3a04f78f174e1e6c2a2ab98bd9a

[ "MIT" ]

28

2020-08-15T08:26:34.000Z

2022-03-17T01:15:52.000Z

from rest_framework import serializers from backend.models.subscribers import Subscriber class SubscribersSerializer(serializers.ModelSerializer): class Meta: model = Subscriber fields = ('name', 'contact_method', 'contact_info')

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ca5b8b888005945b1aadc7c15ef8633a6f76980a

209

py

Python

docs/source/examples/substitutions.py

convexengineering/gpk

c8cf2b30ce1c3d28f135352bd584a0130e903e3f

[ "MIT" ]

76

2017-10-24T18:38:48.000Z

2022-01-13T03:14:37.000Z

docs/source/examples/substitutions.py

convexengineering/gpk

c8cf2b30ce1c3d28f135352bd584a0130e903e3f

[ "MIT" ]

485

2017-09-22T18:31:06.000Z

2022-03-02T20:34:11.000Z

docs/source/examples/substitutions.py

appliedopt/gpkit

647ef0a2a0ff625026943bfd7fb5ca560100898b

[ "MIT" ]

23

2017-12-11T01:29:00.000Z

2022-02-14T07:53:16.000Z

"Example substitution; adapted from t_sub.py/t_NomialSubs /test_Basic" from gpkit import Variable x = Variable("x") p = x**2 assert p.sub({x: 3}) == 9 assert p.sub({x.key: 3}) == 9 assert p.sub({"x": 3}) == 9

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null

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ca6cd101eb285ec0cff7b321427c1e24a9fdfad5

59

py

Python

DSToolbox/cleaning_tools.py

RNEnriquez/DataScience-ToolBox

cb181673b63242f1253d8d078140369769eb06bf

[ "MIT" ]

3

2019-08-14T20:58:00.000Z

2020-03-25T16:42:14.000Z

DSToolbox/cleaning_tools.py

RNEnriquez/DataScience-ToolBox

cb181673b63242f1253d8d078140369769eb06bf

[ "MIT" ]

null

DSToolbox/cleaning_tools.py

RNEnriquez/DataScience-ToolBox

cb181673b63242f1253d8d078140369769eb06bf

[ "MIT" ]

1

2019-10-02T16:32:14.000Z

''' Various tools for cleaning out nulls and imputing '''

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ca7cf913f5feb090e4698977a9edd8dc5becdc7c

526

py

Python

servee/frontendadmin/tests/frontendadmin_registry.py

servee/servee

59405663e1c30d3bcb3f6918932adfc02ae1a668

[ "MIT" ]

3

2017-08-22T13:19:12.000Z

2021-12-28T23:58:17.000Z

servee/frontendadmin/tests/frontendadmin_registry.py

servee/servee

59405663e1c30d3bcb3f6918932adfc02ae1a668

[ "MIT" ]

null

servee/frontendadmin/tests/frontendadmin_registry.py

servee/servee

59405663e1c30d3bcb3f6918932adfc02ae1a668

[ "MIT" ]

null

from django.contrib.flatpages.models import FlatPage from django.contrib.flatpages.admin import FlatPageAdmin import frontendadmin class FlatPageFrontendadminAdmin(FlatPageAdmin, frontendadmin.ServeeModelAdmin): """ This class extends from the normal FlatPageAdmin, as well as frontendadmin.ServeeModelAdmin The later simply adds to the templates that should be processed when looking for the templates to render this page. """ pass frontendadmin.site.register(FlatPage, FlatPageFrontendadminAdmin)

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04ae497d164e29edd2337c15ce4e6474100f390b

51

py

Python

nowcasting_utils/metrics/__init__.py

openclimatefix/nowcasting_utils

7a45e9d24ce29693d96fd9c75a34ca1d205b64bc

[ "MIT" ]

2

2021-12-20T15:56:40.000Z

2022-02-09T07:31:27.000Z

nowcasting_utils/metrics/__init__.py

openclimatefix/nowcasting_utils

7a45e9d24ce29693d96fd9c75a34ca1d205b64bc

[ "MIT" ]

37

2021-09-08T14:36:00.000Z

2022-02-16T20:05:24.000Z

nowcasting_utils/metrics/__init__.py

openclimatefix/nowcasting_utils

7a45e9d24ce29693d96fd9c75a34ca1d205b64bc

[ "MIT" ]

null

""" Metrics used for evaluating various models """

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null

0

1

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04d52126ecb944a8eb132b01cbacc60fe85e28ab

25

py

Python

apps/controllerx/cx_version.py

Digital-Lemon/controllerx

6b90ede37fd7bfaa2771862e326bee48f7650d64

[ "MIT" ]

null

apps/controllerx/cx_version.py

Digital-Lemon/controllerx

6b90ede37fd7bfaa2771862e326bee48f7650d64

[ "MIT" ]

null

apps/controllerx/cx_version.py

Digital-Lemon/controllerx

6b90ede37fd7bfaa2771862e326bee48f7650d64

[ "MIT" ]

null

__version__ = "v4.0.0b3"

12.5

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b6c28b36d0a727aea394b47e8f0557a031ceae6b

5,663

py

Python

mayan/apps/motd/tests/test_api.py

sophiawa/Mayan-EDMS

42f20576d0c690b645a60bf53c5169cda4264231

[ "Apache-2.0" ]

null

mayan/apps/motd/tests/test_api.py

sophiawa/Mayan-EDMS

42f20576d0c690b645a60bf53c5169cda4264231

[ "Apache-2.0" ]

10

2021-03-20T00:01:17.000Z

2022-03-12T00:48:43.000Z

mayan/apps/motd/tests/test_api.py

sophiawa/Mayan-EDMS

42f20576d0c690b645a60bf53c5169cda4264231

[ "Apache-2.0" ]

1

2020-12-17T02:35:09.000Z

from rest_framework import status from mayan.apps.rest_api.tests.base import BaseAPITestCase from ..models import Message from ..permissions import ( permission_message_create, permission_message_delete, permission_message_edit, permission_message_view ) from .literals import ( TEST_LABEL, TEST_LABEL_EDITED, TEST_MESSAGE, TEST_MESSAGE_EDITED ) from .mixins import MOTDTestMixin class MOTDAPITestCase(MOTDTestMixin, BaseAPITestCase): def _request_message_create_view(self): return self.post( viewname='rest_api:message-list', data={ 'label': TEST_LABEL, 'message': TEST_MESSAGE } ) def test_message_create_view_no_permission(self): response = self._request_message_create_view() self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN) self.assertEqual(Message.objects.count(), 0) def test_message_create_view_with_permission(self): self.grant_permission(permission=permission_message_create) response = self._request_message_create_view() self.assertEqual(response.status_code, status.HTTP_201_CREATED) message = Message.objects.first() self.assertEqual(response.data['id'], message.pk) self.assertEqual(response.data['label'], TEST_LABEL) self.assertEqual(response.data['message'], TEST_MESSAGE) self.assertEqual(Message.objects.count(), 1) self.assertEqual(message.label, TEST_LABEL) self.assertEqual(message.message, TEST_MESSAGE) def _request_message_delete_view(self): return self.delete( viewname='rest_api:message-detail', kwargs={ 'pk': self.test_message.pk } ) def test_message_delete_view_no_access(self): self._create_test_message() response = self._request_message_delete_view() self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND) self.assertEqual(Message.objects.count(), 1) def test_message_delete_view_with_access(self): self._create_test_message() self.grant_access( obj=self.test_message, permission=permission_message_delete ) response = self._request_message_delete_view() self.assertEqual(response.status_code, status.HTTP_204_NO_CONTENT) self.assertEqual(Message.objects.count(), 0) def _request_message_detail_view(self): return self.get( viewname='rest_api:message-detail', kwargs={ 'pk': self.test_message.pk } ) def test_message_detail_view_no_access(self): self._create_test_message() response = self._request_message_detail_view() self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND) def test_message_detail_view_with_access(self): self._create_test_message() self.grant_access( obj=self.test_message, permission=permission_message_view ) response = self._request_message_detail_view() self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.data['label'], TEST_LABEL) def _request_message_edit_via_patch_view(self): return self.patch( viewname='rest_api:message-detail', kwargs={ 'pk': self.test_message.pk }, data={ 'label': TEST_LABEL_EDITED, 'message': TEST_MESSAGE_EDITED } ) def test_message_edit_via_patch_view_no_access(self): self._create_test_message() response = self._request_message_edit_via_patch_view() self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND) self.test_message.refresh_from_db() self.assertEqual(self.test_message.label, TEST_LABEL) self.assertEqual(self.test_message.message, TEST_MESSAGE) def test_message_edit_via_patch_view_with_access(self): self._create_test_message() self.grant_access( obj=self.test_message, permission=permission_message_edit ) response = self._request_message_edit_via_patch_view() self.assertEqual(response.status_code, status.HTTP_200_OK) self.test_message.refresh_from_db() self.assertEqual(self.test_message.label, TEST_LABEL_EDITED) self.assertEqual(self.test_message.message, TEST_MESSAGE_EDITED) def _request_message_edit_via_put_view(self): return self.put( viewname='rest_api:message-detail', kwargs={ 'pk': self.test_message.pk }, data={ 'label': TEST_LABEL_EDITED, 'message': TEST_MESSAGE_EDITED } ) def test_message_edit_via_put_view_no_access(self): self._create_test_message() response = self._request_message_edit_via_put_view() self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND) self.test_message.refresh_from_db() self.assertEqual(self.test_message.label, TEST_LABEL) self.assertEqual(self.test_message.message, TEST_MESSAGE) def test_message_edit_via_put_view_with_access(self): self._create_test_message() self.grant_access( obj=self.test_message, permission=permission_message_edit ) response = self._request_message_edit_via_put_view() self.assertEqual(response.status_code, status.HTTP_200_OK) self.test_message.refresh_from_db() self.assertEqual(self.test_message.label, TEST_LABEL_EDITED) self.assertEqual(self.test_message.message, TEST_MESSAGE_EDITED)

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b6dceec2e98b65db9e78348fb3495f6169c8700b

19

py

Python

Week 8_activity/controller/__init__.py

Kenny-WilliamsStockdale/PythonPlay

10c64ceba80fe2d0fc22d11288e5a738199b7f75

[ "MIT" ]

null

Week 8_activity/controller/__init__.py

Kenny-WilliamsStockdale/PythonPlay

10c64ceba80fe2d0fc22d11288e5a738199b7f75

[ "MIT" ]

1

2021-08-10T22:14:55.000Z

Week 8_activity/controller/__init__.py

Kenny-WilliamsStockdale/PythonPlay

10c64ceba80fe2d0fc22d11288e5a738199b7f75

[ "MIT" ]

null

__all__ = ["DES"]

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227

py

Python

task/serializer.py

ruchirs/ratestask

43e411325fec63e68b80ce68210120fc0fe55307

[ "MIT" ]

1

2020-11-19T15:09:23.000Z

task/serializer.py

ruchirs/ratestask

43e411325fec63e68b80ce68210120fc0fe55307

[ "MIT" ]

null

task/serializer.py

ruchirs/ratestask

43e411325fec63e68b80ce68210120fc0fe55307

[ "MIT" ]

null

from rest_framework import serializers from .models import Prices class PriceSerializer(serializers.ModelSerializer): class Meta: model = Prices fields = ('date', 'origin_code', 'destination_code', 'price')

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8e360fac589a3025f974276b7180bd86ec6dbd6d

405

py

Python

utils/open_sites.py

SrGambiarra/KivyStudioDesigner

7f617b60aef3d5e99865cb559b9b5ee93a1988f5

[ "MIT" ]

3

2022-03-05T21:54:34.000Z

2022-03-15T12:55:45.000Z

utils/open_sites.py

SrGambiarra/KivyStudioDesigner

7f617b60aef3d5e99865cb559b9b5ee93a1988f5

[ "MIT" ]

2

2022-03-13T04:15:47.000Z

2022-03-30T11:51:41.000Z

utils/open_sites.py

SrGambiarra/KivyStudioDesigner

7f617b60aef3d5e99865cb559b9b5ee93a1988f5

[ "MIT" ]

null

import webbrowser def open_repo(*args): ''' Open the Kivy Designer repository ''' webbrowser.open("https://github.com/kivy/kivy-designer") def open_docs(*args): ''' Open the Kivy docs ''' webbrowser.open("http://kivy.org/docs/") def open_kd_docs(*args): ''' Open the Kivy Designer documentation ''' webbrowser.open("http://kivy-designer.readthedocs.org")

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0

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8e36e19c53569556966794ddee38664662296f13

241

py

Python

toontown/ai/HolidayBaseAI.py

LittleNed/toontown-stride

1252a8f9a8816c1810106006d09c8bdfe6ad1e57

[ "Apache-2.0" ]

3

2020-01-02T08:43:36.000Z

2020-07-05T08:59:02.000Z

toontown/ai/HolidayBaseAI.py

NoraTT/Historical-Commits-Project-Altis-Source

fe88e6d07edf418f7de6ad5b3d9ecb3d0d285179

[ "Apache-2.0" ]

null

toontown/ai/HolidayBaseAI.py

NoraTT/Historical-Commits-Project-Altis-Source

fe88e6d07edf418f7de6ad5b3d9ecb3d0d285179

[ "Apache-2.0" ]

4

2019-06-20T23:45:23.000Z

2020-10-14T20:30:15.000Z

from direct.directnotify.DirectNotifyGlobal import * class HolidayBaseAI: def __init__(self, air, holidayId): self.air = air self.holidayId = holidayId def start(self): pass def stop(self): pass

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0

4

8e48285ab1fdbab0ce5fd0cf1095c92ebb0fc537

2,138

py

Python

src/scs_core/aws/data/http_response.py

south-coast-science/scs_core

81ad4010abb37ca935f3a31ac805639ef53b1bcf

[ "MIT" ]

3

2019-03-12T01:59:58.000Z

2020-09-12T07:27:42.000Z

src/scs_core/aws/data/http_response.py

south-coast-science/scs_core

81ad4010abb37ca935f3a31ac805639ef53b1bcf

[ "MIT" ]

1

2018-04-20T07:58:38.000Z

2021-03-27T08:52:45.000Z

src/scs_core/aws/data/http_response.py

south-coast-science/scs_core

81ad4010abb37ca935f3a31ac805639ef53b1bcf

[ "MIT" ]

4

2017-09-29T13:08:43.000Z

2019-10-09T09:13:58.000Z

""" Created on 23 Apr 2021 @author: Bruno Beloff (bruno.beloff@southcoastscience.com) https://docs.python.org/3/library/http.html https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS """ from abc import ABC from http import HTTPStatus from scs_core.data.json import JSONable, JSONify # -------------------------------------------------------------------------------------------------------------------- class HTTPResponse(JSONable, ABC): """ classdocs """ __CORS_HEADERS = { # Cross-Origin Resource Sharing 'Access-Control-Allow-Origin': '*', 'Access-Control-Allow-Credentials': True, } # ---------------------------------------------------------------------------------------------------------------- def __init__(self, status, reason=None): """ Constructor """ self.__status = status # HTTPStatus member self.__reason = reason # string # ---------------------------------------------------------------------------------------------------------------- def is_ok(self): return self.status == HTTPStatus.OK # ---------------------------------------------------------------------------------------------------------------- def as_http(self, cors=False): jdict = { 'statusCode': self.status.value, 'body': JSONify.dumps(self) } if cors: jdict['headers'] = self.__CORS_HEADERS return jdict def as_json(self): return {'statusCode': self.status.value} # ---------------------------------------------------------------------------------------------------------------- @property def status(self): return self.__status @property def reason(self): return self.__reason # ---------------------------------------------------------------------------------------------------------------- def __str__(self, *args, **kwargs): return "HTTPResponse:{status:%s, reason:%s}" % (self.status, self.reason)

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8e503607f525fe8b7db40e876ce2139a6a8bde5e

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py

Python

configurations/auth.py

ValentineSean/product-catalog-api

7bd50555eba390a25920983daf01ee05a89cbf5f

[ "Apache-2.0" ]

null

configurations/auth.py

ValentineSean/product-catalog-api

7bd50555eba390a25920983daf01ee05a89cbf5f

[ "Apache-2.0" ]

null

configurations/auth.py

ValentineSean/product-catalog-api

7bd50555eba390a25920983daf01ee05a89cbf5f

[ "Apache-2.0" ]

null

from flask_jwt_extended import JWTManager from flask_bcrypt import Bcrypt jwt = JWTManager() bcrypt = Bcrypt()

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f3dee8d4b998b40b2167ddd645732a0ad3fd79fb

9,930

py

Python

examples/ui/twente_temperature.py

abhishekgahlot/flexx

27a995603b5e9d758f9d38eababcc626aa661299

[ "BSD-2-Clause" ]

1

2015-11-05T19:17:37.000Z

examples/ui/twente_temperature.py

abhishekgahlot/flexx

27a995603b5e9d758f9d38eababcc626aa661299

[ "BSD-2-Clause" ]

null

examples/ui/twente_temperature.py

abhishekgahlot/flexx

27a995603b5e9d758f9d38eababcc626aa661299

[ "BSD-2-Clause" ]

null

""" Examample data-viz app. It shows real temperature data from the region where I live. The data are monthly average temperatures for the pas 65 years. The month can be selected with a slider. Via another slider, the data can be smoothed so the upward trend can be made more apparent. This app can be exported to a standalone HTML document. """ from flexx import app, ui, react # Raw data obtained from # http://www.knmi.nl/klimatologie/maandgegevens/datafiles/mndgeg_290_tg.txt raw_data = """ Deze gegevens mogen vrij worden gebruikt mits de volgende bronvermelding wordt gegeven: KONINKLIJK NEDERLANDS METEOROLOGISCH INSTITUUT (KNMI) These data can be used freely provided that the following source is acknowledged: ROYAL NETHERLANDS METEOROLOGICAL INSTITUTE MAAND- en JAARGEMIDDELDE TEMPERATUREN (0.1 graden Celsius) MONTHLY AND YEARLY MEAN TEMPERATURES (0.1 degrees Celsius) STN = stationsnummer / WMO-number = 06... (235=De Kooy,240=Schiphol,260=De Bilt,270=Leeuwarden,280=Eelde, 290=Twenthe,310=Vlissingen,344=Rotterdam,370=Eindhoven,380=Maastricht) STN,YYYY, JAN, FEB, MAR, APR, MAY, JUN, JUL, AUG, SEP, OCT, NOV, DEC, YEAR 290,1951, 35, 35, 34, 74, 120, 154, 169, 171, 155, 85, 82, 44, 97 290,1952, 19, 20, 43, 107, 129, 149, 172, 173, 111, 80, 23, 10, 86 290,1953, 11, 15, 47, 91, 133, 162, 170, 167, 140, 115, 71, 48, 98 290,1954, -11, -10, 57, 65, 128, 156, 142, 160, 138, 116, 65, 51, 88 290,1955, -1, -5, 16, 82, 100, 146, 179, 181, 146, 92, 58, 42, 86 290,1956, 17, -71, 50, 50, 127, 130, 166, 140, 146, 94, 46, 49, 79 290,1957, 32, 49, 80, 83, 102, 166, 176, 156, 124, 107, 60, 24, 97 290,1958, 16, 32, 15, 62, 129, 148, 168, 177, 157, 109, 54, 44, 93 290,1959, 12, 7, 72, 103, 131, 164, 192, 180, 156, 111, 52, 39, 102 290,1960, 21, 25, 55, 88, 130, 161, 153, 155, 133, 107, 73, 26, 94 290,1961, 14, 61, 71, 104, 106, 157, 152, 158, 172, 114, 45, 8, 97 290,1962, 31, 21, 14, 80, 99, 135, 145, 152, 127, 104, 39, -14, 78 290,1963, -63, -38, 45, 91, 112, 158, 165, 153, 137, 91, 81, -15, 76 290,1964, -1, 28, 23, 91, 143, 156, 169, 161, 142, 78, 58, 20, 89 290,1965, 24, 11, 37, 76, 117, 150, 147, 152, 131, 98, 19, 38, 83 290,1966, -3, 37, 46, 87, 135, 171, 155, 158, 134, 111, 38, 36, 92 290,1967, 32, 48, 64, 70, 128, 146, 181, 163, 141, 116, 47, 25, 97 290,1968, 7, 13, 59, 95, 106, 155, 161, 168, 142, 111, 50, -7, 88 290,1969, 37, -7, 13, 77, 129, 145, 175, 168, 137, 115, 60, -25, 85 290,1970, -4, 4, 21, 56, 125, 170, 154, 165, 136, 99, 72, 18, 85 290,1971, 22, 32, 23, 78, 138, 138, 170, 171, 125, 97, 46, 50, 91 290,1972, -3, 34, 61, 71, 116, 137, 172, 151, 108, 82, 53, 32, 85 290,1973, 23, 23, 49, 54, 119, 160, 171, 176, 145, 83, 49, 23, 90 290,1974, 51, 42, 55, 85, 112, 143, 147, 164, 129, 64, 62, 66, 93 290,1975, 62, 27, 43, 69, 108, 147, 176, 195, 148, 77, 45, 23, 93 290,1976, 26, 19, 22, 71, 129, 173, 188, 170, 134, 107, 61, 7, 92 290,1977, 22, 45, 68, 60, 117, 143, 161, 158, 126, 114, 61, 42, 93 290,1978, 27, 2, 61, 67, 121, 145, 150, 147, 136, 110, 66, 13, 87 290,1979, -39, -22, 41, 73, 116, 150, 150, 151, 125, 96, 45, 46, 78 290,1980, -8, 38, 38, 74, 115, 145, 153, 166, 146, 87, 42, 29, 85 290,1981, 16, 9, 81, 87, 138, 147, 163, 164, 148, 85, 60, -10, 91 290,1982, 3, 23, 50, 71, 122, 161, 186, 169, 160, 112, 76, 31, 97 290,1983, 57, 0, 56, 89, 111, 159, 191, 174, 134, 94, 54, 27, 96 290,1984, 23, 14, 33, 71, 100, 129, 150, 168, 124, 109, 73, 35, 86 290,1985, -46, -14, 35, 81, 132, 131, 165, 150, 132, 97, 17, 52, 78 290,1986, 16, -46, 45, 68, 137, 160, 162, 151, 105, 109, 77, 41, 85 290,1987, -40, 17, 13, 103, 99, 137, 163, 155, 145, 104, 61, 38, 83 290,1988, 58, 42, 43, 81, 144, 145, 160, 166, 139, 104, 53, 55, 99 290,1989, 41, 48, 77, 65, 138, 159, 178, 171, 154, 122, 50, 44, 104 290,1990, 50, 73, 79, 84, 138, 151, 161, 182, 122, 119, 54, 35, 104 290,1991, 29, -9, 83, 81, 97, 126, 188, 173, 147, 94, 50, 32, 91 290,1992, 22, 47, 64, 83, 154, 170, 182, 180, 143, 73, 74, 33, 102 290,1993, 42, 12, 51, 112, 142, 152, 157, 146, 125, 86, 15, 44, 90 290,1994, 44, 6, 70, 81, 123, 151, 213, 174, 133, 86, 87, 48, 101 290,1995, 27, 60, 46, 89, 124, 145, 200, 187, 136, 124, 55, -16, 98 290,1996, -16, -10, 23, 89, 106, 151, 161, 175, 115, 99, 52, -6, 78 290,1997, -17, 58, 72, 70, 124, 157, 173, 201, 134, 89, 57, 41, 97 290,1998, 43, 57, 67, 90, 144, 155, 159, 160, 144, 90, 29, 35, 98 290,1999, 45, 26, 66, 97, 135, 149, 188, 172, 177, 101, 59, 41, 105 290,2000, 37, 52, 63, 102, 145, 160, 152, 169, 150, 111, 77, 46, 105 290,2001, 22, 37, 42, 79, 140, 147, 183, 183, 128, 140, 61, 21, 99 290,2002, 39, 65, 64, 89, 135, 167, 174, 186, 139, 86, 71, 16, 103 290,2003, 16, 7, 68, 93, 134, 179, 185, 193, 139, 66, 78, 33, 99 290,2004, 27, 40, 53, 103, 116, 152, 165, 188, 149, 110, 54, 27, 99 290,2005, 43, 14, 58, 102, 125, 162, 176, 157, 152, 129, 61, 33, 101 290,2006, 4, 18, 32, 85, 143, 168, 222, 159, 177, 136, 88, 62, 108 290,2007, 61, 54, 74, 125, 139, 174, 169, 168, 133, 93, 61, 31, 107 290,2008, 59, 47, 53, 83, 150, 164, 180, 173, 131, 97, 62, 18, 101 290,2009, 1, 26, 55, 125, 137, 153, 178, 182, 144, 93, 94, 17, 100 290,2010, -17, 9, 58, 93, 100, 164, 204, 164, 126, 95, 52, -27, 85 290,2011, 27, 36, 52, 124, 138, 162, 158, 168, 152, 106, 60, 55, 103 290,2012, 36, 1, 77, 82, 145, 145, 169, 184, 134, 96, 64, 41, 98 290,2013, 15, 9, 12, 82, 116, 154, 188, 179, 138, 118, 59, 55, 94 290,2014, 48, 64, 81, 118, 127, 157, 195, 157, 153, 132, 80, 41, 113 """ def parse_data(raw_data): years, data = [], [[] for i in range(13)] for line in raw_data.splitlines(): if line.startswith('290'): parts = [int(i.strip()) for i in line.split(',')] years.append(parts[1]) for i in range(13): data[i].append(parts[i+2]/10.0) return years, data years, data = parse_data(raw_data) @app.serve class Twente(ui.Widget): def init(self): with ui.HBox(): ui.Widget(flex=1) with ui.VBox(): with ui.Panel(title='Plot options'): with ui.VBox(): self.month_label = ui.Label(text='Month') self.month = ui.Slider(max=12, step=1) self.smoothing_label = ui.Label(text='Smoothing') self.smoothing = ui.Slider(max=20, step=2) ui.Widget(flex=1) with ui.VBox(): self.plot = ui.PlotWidget(size=(640, 480), xdata=years, yrange=(-5, 20), title='Average monthly temperature', xlabel='year', ylabel='temperature (°C)') ui.Widget(flex=1) ui.Widget(flex=1) class JS: data = data months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec', 'total'] @react.connect('month.value', 'smoothing.value') def _update_plot(self, month, smoothing): self.month_label.text('Month (%s)' % self.months[month]) self.smoothing_label.text('Smoothing (%i)' % smoothing) yy1 = self.data[month] yy2 = [] sm2 = int(smoothing / 2) for i in range(len(yy1)): val = 0 n = 0 for j in range(max(0, i-sm2), min(len(yy1), i+sm2+1)): val += yy1[j] n += 1 if n == 0: yy2.append(yy1[i]) else: yy2.append(val / n) self.plot.ydata(yy2) if __name__ == '__main__': m = app.launch(Twente, title='Temperature 1951 - 2014', size=(900, 400)) m.bgcolor('#eee') # more desktop-like app.run()

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f3e4a15c6cb96e12cf5361e321a719f097854df1

5,948

py

Python

DailyProgrammer/DP20160926A.py

DayGitH/Python-Challenges

bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf

[ "MIT" ]

2

2020-12-23T18:59:22.000Z

2021-04-14T13:16:09.000Z

DailyProgrammer/DP20160926A.py

DayGitH/Python-Challenges

bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf

[ "MIT" ]

null

DailyProgrammer/DP20160926A.py

DayGitH/Python-Challenges

bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf

[ "MIT" ]

null

""" [2016-09-26] Challenge #285 [Easy] Cross Platform/Language Data Encoding part 1 https://www.reddit.com/r/dailyprogrammer/comments/54lu54/20160926_challenge_285_easy_cross/ We will make a binary byte oriented encoding of data that is self describing and extensible, and aims to solve the following problems: * portability between 32 and 64 (and any other) bit systems, and languages, and endian-ness. * type system independent of underlying language. * Allow heterogeneous arrays (differing types of array elements) where the underlying language has poor support for them. * leverage power of homogeneous arrays in a language. * support records regardless of underlying language (array of records is homogeneous, even though a record is a heterogeneous list of fields) * Allow ragged arrays (a table where each row is a list, but the rows do not have a uniform size (or shape)) * Provide basic in memory compression. Allow deferred decoding of partial data. # 1. base64 encoding (used in later challenges) To read and write binary data on reddit, we will use base64 encoding, https://www.reddit.com/r/dailyprogrammer/comments/4xy6i1/20160816_challenge_279_easy_uuencoding/ # 2. Extendible byte base. Any size integer can be coded into a variable byte array by using the maximum byte value as a marker to add the next byte value to decode the total. This is useful for coding numbers that you think can be limited to around 255 or close to it, without being "hard constrained" by that limit. "256 possible op codes (or characters) ought to be enough for everyone forever thinking" **unsigned byte input** 12 255 256 510 512 44 1024 last input is a list of 3 integers to encode **sample outputs** 12 255 0 255 1 255 255 0 255 255 2 44 255 255 255 255 4 every element that is not 255 marks the end of "that integer" in a list. You should also write a decoder that transforms output into input. # 3. multibyte and variable byte encodings Instead of a single byte target encoding, 2,4,8 and variable defined byte sizes are also desirable to cover integers with larger ranges. An account balance might have a 40 bit practical limit, but you might not guarantee it forever. 64 bits might not be enough for Zimbabwe currency balances for example. For compressing a list of numbers, often it is useful to set the whole list to one "byte size". Other choices include, * setting an enum/table of possible byte size codings of 1 2 4 8 sizes, and then encoding, the number of elements, the table/enum size and definition, and then 2 lists (enum key, data items) * interleave bytesize, data The latter will often be longer for long lists, but does not encode the table so is simpler to encode/decode. **Encoding format for table definition:** 1. 4 bytes: first 30 bits - length of list. last 2 bits: key into 1 2 4 8. If first 30 bits are max value, then following 4 bytes are added to count until a non-max value is taken. Similar to challenge #2. 2. list of byte lengths defined by key in 1. If last 2 bits of 1 are 3 (signifies up to 8 distinct integer sizes), then this list has 8 items. If there only 6 distinct integer size codings, then the last 2 items in this list would be ignored and set to 0. Values over 255 are encoded as in challenge 2. 3. list of ordered data encodings in boolean form, if there are more than 1. 1 bit for 2, 2 bits for 4, 3 bits for 8. 4. list of data elements. **challenges** encode list of integers from 0 to 1025 using 8 or 16 bit variable encoding. With the shortest encoding that will contain the number. Just print the sum of all the bytes as result for output brevity. **solution** 1. first 4 bytes are (1025 * 4) + 1 (leading 0 bytes for smaller than "full size" numbers) 2. 2 byte list: 1 2 3. 0 for first 256 bits, 1 for remaining bits (total 1032 bits long with padding) 4. 256 + (769 * 2) bytes long encoding of the numbers. # 4. balanced signed numbers Some numbers are negative. The common computer encoding for signed number ranges is to subtract half the max power of 2 from the value. A signed byte has range -128 to 127, where a 0 value corresponds to -128 (in our encoding). For numbers outside this range encoded in a single byte, the process is to take the first byte to determine the sign, and then following bytes add or subtract up to 255 per byte until a non 255 value is reached. # 5. unbalanced signed numbers Instead of the midpoint marking 0, a byte can encode a value within any defined range. Another important application is to use "negative" numbers as codes of some sort. These include: * An expectation that negative numbers are less frequent and smaller relative to 0 * coding special values such as null, infinity, undeterminable (0/0) * Using codes to hint at extended byte encodings and sign of the number, or even data type **sample 0 index codes** (for 16 reserved codes) (new paragraph for multiline explained codes) Null Infinity Negative Infinity Negative 1 byte Negative 2 bytes Negative 4 bytes Negative 8 bytes Negative custom byte length (value is encoded into 2 numbers. First is byte length (in 255 terminated bytes, followed by that number of bytes to represent the number) Positive 1 byte (first number indicates range of 468 to 723). 467 could have been encoded as 255 254 without this special code. Positive 2 byte Positive 4 byte Positive 8 byte Positive 16 byte Positive 64 byte Positive custom byte length (3 to 262 excluding other defined lengths) Positive custom 2 byte length (16 bit unsigned number defines byte length of number, followed by encoded number) **sample inputs** 10 123123 -55 Null **sample output** 26 9 123123 3 54 (minimum range value is -1) 0 **challenge input** 192387198237192837192837192387123817239182737 _44 981237123 array of 3 numbers (_44 is -44) to be encoded """ def main(): pass if __name__ == "__main__": main()

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156

py

Python

pm4pymdl/algo/mvp/gen_framework/edge_freq/__init__.py

dorian1000/pm4py-mdl

71e0c2425abb183da293a58d31e25e50137c774f

[ "MIT" ]

5

2021-01-31T22:45:29.000Z

2022-02-22T14:26:06.000Z

pm4pymdl/algo/mvp/gen_framework/edge_freq/__init__.py

Javert899/pm4py-mdl

4cc875999100f3f1ad60b925a20e40cf52337757

[ "MIT" ]

3

2021-07-07T15:32:55.000Z

2021-07-07T16:15:36.000Z

pm4pymdl/algo/mvp/gen_framework/edge_freq/__init__.py

dorian1000/pm4py-mdl

71e0c2425abb183da293a58d31e25e50137c774f

[ "MIT" ]

9

2020-09-23T15:34:11.000Z

2022-03-17T09:15:40.000Z

from pm4pymdl.algo.mvp.gen_framework.edge_freq import edge_freq_builder, type11, type12, type13, type211, type212, type221, \ type222, type231, type232

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6d2b872bff6c9060195409fbdcef0db70610fac6

151

py

Python

sandbox/lib/jumpscale/JumpscaleLibs/clients/gitea/GiteaRepoForNonOwner.py

threefoldtech/threebot_prebuilt

1f0e1c65c14cef079cd80f73927d7c8318755c48

[ "Apache-2.0" ]

null

sandbox/lib/jumpscale/JumpscaleLibs/clients/gitea/GiteaRepoForNonOwner.py

threefoldtech/threebot_prebuilt

1f0e1c65c14cef079cd80f73927d7c8318755c48

[ "Apache-2.0" ]

117

2019-09-01T11:59:19.000Z

2020-07-14T11:10:08.000Z

sandbox/lib/jumpscale/JumpscaleLibs/clients/gitea/GiteaRepoForNonOwner.py

threefoldtech/threebot_prebuilt

1f0e1c65c14cef079cd80f73927d7c8318755c48

[ "Apache-2.0" ]

2

2020-04-06T15:21:23.000Z

2020-05-07T04:29:53.000Z

import json from Jumpscale import j from .GiteaRepo import GiteaRepo JSBASE = j.baseclasses.object class GiteaRepoForNonOwner(GiteaRepo): pass

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6d3bc7320a841574284a3da1dffa188fee310518

2,330

py

Python

vacker/media/media.py

MatthewJohn/vacker

96746a20041035a87cb64518a9f1d3e4b3a46df4

[ "Apache-2.0" ]

1

2022-01-24T04:46:14.000Z

vacker/media/media.py

MatthewJohn/vacker

96746a20041035a87cb64518a9f1d3e4b3a46df4

[ "Apache-2.0" ]

17

2017-10-14T11:40:45.000Z

2022-03-12T13:16:31.000Z

vacker/media/media.py

MatthewJohn/vacker

96746a20041035a87cb64518a9f1d3e4b3a46df4

[ "Apache-2.0" ]

null

from bson.objectid import ObjectId import datetime import vacker.file_factory import vacker.database import vacker.config from vacker.media import File class Media(File): def update_sets(self): if not self.get_date(): return database_connection = vacker.database.Database.get_database() file_factory = vacker.file_factory.FileFactory() surround_media = file_factory.get_media_date_range( self.get_date(), datetime.timedelta(seconds=vacker.config.Config.get('DEFAULT_SET_INTERVAL')) ) surround_media.sort(key=lambda x: x['datetime']) sets = [x['set_id'] for x in surround_media if x['set_id'] is not None] # Create set/get set ID and update all media set_id = sets[0] if len(sets) else database_connection.sets.insert_one({'auto': True, 'backup_state': False, 'name': '', 'hidden': False}).inserted_id database_connection.media.update({'_id': {'$in': [x['_id'] for x in surround_media]}}, {'$set': {'set_id': set_id}}, multi=True) database_connection.media.update({'set_id': {'$in': sets}}, {'$set': {'set_id': set_id}}, multi=True) def update_events(self): if not self.get_date(): return database_connection = vacker.database.Database.get_database() file_factory = vacker.file_factory.FileFactory() surround_media = file_factory.get_media_date_range( self.get_date(), datetime.timedelta(seconds=vacker.config.Config.get('DEFAULT_EVENT_INTERVAL')) ) surround_media.sort(key=lambda x: x['datetime']) events = [x['event_id'] for x in surround_media if x['event_id'] is not None] # Create set/get set ID and update all media event_id = events[0] if len(events) else database_connection.events.insert_one({'auto': True, 'backup_state': False, 'name': '', 'hidden': False}).inserted_id database_connection.media.update({'_id': {'$in': [x['_id'] for x in surround_media]}}, {'$set': {'event_id': event_id}}, multi=True) database_connection.media.update({'set_id': {'$in': events}}, {'$set': {'event_id': event_id}}, multi=True)

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6d477c07768ce0f1e99a8a613ebd411b3ecf72e9

839

py

Python

src/boardcomputer/frontend/WebStream.py

eddex/pren2

336afade5a6f46eb955b1e9c0c1e5ebda9e19b9b

[ "MIT" ]

null

src/boardcomputer/frontend/WebStream.py

eddex/pren2

336afade5a6f46eb955b1e9c0c1e5ebda9e19b9b

[ "MIT" ]

null

src/boardcomputer/frontend/WebStream.py

eddex/pren2

336afade5a6f46eb955b1e9c0c1e5ebda9e19b9b

[ "MIT" ]

null

import socketio class WebStream: def __init__(self, url: str): """ Interface for Logging on Web Server Args: url: URL of Webserver 'http://192.168.10.1:5000' """ self.sio = socketio.Client() self.sio.connect('http://192.168.10.1:5000') def write(self, msg): self.sio.emit('message', msg) def flush(self): pass def close(self): self.sio.disconnect() class WebLoggerStream: def __init__(self, socket): """ Interface for Logging on Web Server Args: socket: URL of Webserver 'http://192.168.10.1:5000' """ self.sio = socket def write(self, msg): self.sio.emit('message', msg) def flush(self): pass def close(self): self.sio.disconnect()

18.644444

63

0.543504

103

839

4.349515

0.359223

0.109375

0.066964

0.080357

0.720982

0.683036

0.53125

0

0.069272

0.328963

839

44

64

19.068182

0.726465

0.231228

0

0.6

0

0.067138

0

1

0.4

false

0.1

0.05

0

0.55

0

null

0

1

0

null

0

1

0

1

0

1

0

4

6d47f0eb39c1922df58cb4141cabcf1e0054d386

320

py

Python

Python/Network_Programming.py

mmoccaro/Network_Programming

58c40574a7cb54eaa7b30bdf510d51bb891acd45

[ "Apache-2.0" ]

null

Python/Network_Programming.py

mmoccaro/Network_Programming

58c40574a7cb54eaa7b30bdf510d51bb891acd45

[ "Apache-2.0" ]

null

Python/Network_Programming.py

mmoccaro/Network_Programming

58c40574a7cb54eaa7b30bdf510d51bb891acd45

[ "Apache-2.0" ]

null

# * ======================= # * # * Author: Matthew Moccaro # * File: Network_Programming.py # * Type: Python Source File # * # * Creation Date: 1/2/19 # * # * Description: Python # * source file for the # * network programming # * project. # * # * ====================== print("Network Programming For Python")

18.823529

39

0.534375

30

320

5.666667

0.666667

0.317647

0.188235

0

0.015564

0.196875

320

16

40

20

0.645914

0.78125

0

0.545455

0

1

0

true

0

1

0

null

1

0

null

0

1

0

1

0

4

6d4e55cf1cf620ffb5944f026fd8cdd1d8f92853

60

py

Python

code/CM1_affiche.py

christophesaintjean/IntroProgS1_2020

99555d1e3681d88ee023592a16caecdec6f7c0b4

[ "CC0-1.0" ]

null

code/CM1_affiche.py

christophesaintjean/IntroProgS1_2020

99555d1e3681d88ee023592a16caecdec6f7c0b4

[ "CC0-1.0" ]

null

code/CM1_affiche.py

christophesaintjean/IntroProgS1_2020

99555d1e3681d88ee023592a16caecdec6f7c0b4

[ "CC0-1.0" ]

null

print("Mon premier") print("programme") print("est affiche")

20

0.733333

8

60

5.5

0.75

0

0.066667

60

3

21

20

0.785714

0

0.508197

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6d55705e682bea97b396a5838e11febf6a5504e9

158

py

Python

sht_sensor/__main__.py

mk-fg/sht-sensor

5a8f2fd7ca874d275f6890a55f7dc94ee8b04dd6

[ "WTFPL" ]

13

2015-11-04T16:39:31.000Z

2018-09-08T19:07:39.000Z

sht_sensor/__main__.py

mk-fg/sht-sensor

5a8f2fd7ca874d275f6890a55f7dc94ee8b04dd6

[ "WTFPL" ]

9

2016-02-05T19:20:08.000Z

2018-03-31T05:11:19.000Z

sht_sensor/__main__.py

kizniche/sht-sensor

e44758327eec781297e68f3f59b6937b7c5758e3

[ "WTFPL" ]

3

2015-11-02T21:58:07.000Z

2018-03-31T01:19:22.000Z

# -*- coding: utf-8 -*- from __future__ import print_function from sht_sensor.sensor import main import os, sys if __name__ == '__main__': sys.exit(main())

19.75

43

0.721519

23

158

4.347826

0.695652

0

0.007407

0.14557

158

7

44

22.571429

0.733333

0.132911

0

0.059259

0

1

0

true

0

0.75

0

0.75

0.25

1

0

null

0

1

0

null

0

1

0

1

0

4

6d55a2e77bdf23d00009f5ba560ff82d1226f63c

234

py

Python

asynctb/__init__.py

shamrin/asynctb

d06a77cb2e496108e73adc65e27d1d313592685a

[ "Apache-2.0", "MIT" ]

6

2020-07-02T16:43:15.000Z

2021-11-29T06:30:57.000Z

asynctb/__init__.py

shamrin/asynctb

d06a77cb2e496108e73adc65e27d1d313592685a

[ "Apache-2.0", "MIT" ]

2

2020-07-02T09:00:50.000Z

2020-07-26T06:39:09.000Z

asynctb/__init__.py

shamrin/asynctb

d06a77cb2e496108e73adc65e27d1d313592685a

[ "Apache-2.0", "MIT" ]

2

2020-07-05T01:25:37.000Z

2021-01-26T08:00:06.000Z

from ._version import __version__ from ._traceback import FrameInfo, Traceback from ._registry import ( register_unwrap_awaitable, register_unwrap_context_manager, register_get_target, customize, ) from . import _glue

23.4

44

0.790598

26

234

6.538462

0.576923

0.164706

0

0.162393

234

9

45

26

0.867347

0

1

0

true

0

0.444444

0

0.444444

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ed914a2d738e15f32235a6cdd6eb054c4244ed44

100

py

Python

createTrend/Views_Predict/apps.py

junkwon-dev/createTrend_backend

8ec550c4c5d38f898ad0285045a57e50ad30fcdb

[ "MIT", "Apache-2.0", "BSD-3-Clause" ]

null

createTrend/Views_Predict/apps.py

junkwon-dev/createTrend_backend

8ec550c4c5d38f898ad0285045a57e50ad30fcdb

[ "MIT", "Apache-2.0", "BSD-3-Clause" ]

null

createTrend/Views_Predict/apps.py

junkwon-dev/createTrend_backend

8ec550c4c5d38f898ad0285045a57e50ad30fcdb

[ "MIT", "Apache-2.0", "BSD-3-Clause" ]

null

from django.apps import AppConfig class ViewsPredictConfig(AppConfig): name = 'Views_Predict'

16.666667

36

0.78

11

100

7

0.909091

0

0.15

100

5

37

20

0.905882

0

0.13

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6109d7f30755e74e960aa4b12f2fc1fefd4b43f2

40

py

Python

coders.py

shabd07/Python-code

63538c393ea05ad5d49599b944d8babd9dcf2a61

[ "MIT" ]

null

coders.py

shabd07/Python-code

63538c393ea05ad5d49599b944d8babd9dcf2a61

[ "MIT" ]

null

coders.py

shabd07/Python-code

63538c393ea05ad5d49599b944d8babd9dcf2a61

[ "MIT" ]

null

a = input("enter your name: ") print(a)

20

31

0.625

7

40

3.571429

0.857143

0

0.175

40

2

32

20

0.757576

0

0.425

0

1

0

false

0

0.5

1

0

null

0

1

0

null

0

1

0

4

610f5b5b4f29fdbf051dfd4b439275a2c68a1464

1,735

py

Python

resp_base/Constraints.py

probablytom/msci-model

243f35dcfb1cb3704140e7616e0e767958875a08

[ "MIT" ]

null

resp_base/Constraints.py

probablytom/msci-model

243f35dcfb1cb3704140e7616e0e767958875a08

[ "MIT" ]

null

resp_base/Constraints.py

probablytom/msci-model

243f35dcfb1cb3704140e7616e0e767958875a08

[ "MIT" ]

null

from abc import ABCMeta from theatre_ag.theatre_ag import SynchronizingClock class ImproperImportanceResetError(Exception): pass class AbstractConstraint: __metaclass__ = ABCMeta def __init__(self, factors: dict): self.factors = factors self.outcome = None self.interpreted = False self.original_importance = None self.importance = None def assign_importance(self, importance): self.original_importance = self.importance self.importance = importance # Only assign if we haven't already. if self.original_importance is None: self.original_importance = importance # If this is the first assignment, keep track of the true original importance self.interpreted = True def reset_importance(self, new_score=None): self.importance = self.original_importance self.original_importance = None self.interpreted = False if new_score is not None: self.assign_importance(new_score) def record_outcome(self, outcome): self.outcome = outcome class Deadline(AbstractConstraint): def __init__(self, duration: int, timeline: SynchronizingClock): super().__init__({}) # Deadlines have only one factor, which is special # This needs to be changed to time assigned self.time_created = timeline.current_tick self.timeline = timeline self.duration = duration # TODO: REMOVE THIS IN FAVOUR OF AGENT-BASED EVALUATION def evaluate(self): return self.factors['length'] < \ (self.timeline.current_tick - self.time_created) class ResourceDelta(AbstractConstraint): pass

29.913793

128

0.675504

191

1,735

5.95288

0.397906

0.098505

0.116095

0.084433

0.119613

0.070361

0

0.259942

1,735

57

129

30.438596

0.885514

0.146974

0

0.153846

0

0.004071

0

0.017544

0

1

0.153846

false

0.051282

0.358974

0.025641

0.666667

0

null

0

null

0

1

0

1

0

1

0

4

61173c64f4145849e07e11a002f4c8c1b30c97c9

91

py

Python

Variables/3.2.5.py

ferrerinicolas/python_samples

107cead4fbee30b275a5e2be1257833129ce5e46

[ "MIT" ]

null

Variables/3.2.5.py

ferrerinicolas/python_samples

107cead4fbee30b275a5e2be1257833129ce5e46

[ "MIT" ]

null

Variables/3.2.5.py

ferrerinicolas/python_samples

107cead4fbee30b275a5e2be1257833129ce5e46

[ "MIT" ]

null

string_variable = "Nicolas" int_variable = 24 print(string_variable) print(int_variable)

13

27

0.802198

12

91

5.75

0.5

0.405797

0

0.024691

0.10989

91

6

28

15.166667

0.82716

0

0.077778

0

1

0

false

0

0.5

1

0

null

1

0

1

0

null

0

1

0

4

b61f14f815014a78519cd75e692e7a2c8852b020

37

py

Python

tests/services/simple_argument.py

berry-langerak/nanoinject

fc24df7534695fda5e0f078f3f9dd6f8861dcb65

[ "MIT" ]

null

tests/services/simple_argument.py

berry-langerak/nanoinject

fc24df7534695fda5e0f078f3f9dd6f8861dcb65

[ "MIT" ]

1

2020-03-25T09:58:28.000Z

tests/services/simple_argument.py

berry-langerak/nanoinject

fc24df7534695fda5e0f078f3f9dd6f8861dcb65

[ "MIT" ]

null

class SimpleArgument: answer = 42

18.5

21

0.72973

4

37

6.75

1

0

0.068966

0.216216

37

2

22

18.5

0.862069

0

1

0

false

0

1

0

1

0

null

0

1

0

null

0

1

0

4

b6207b39004c8dafcf759f850fefcb23711a3ba5

19

py

Python

src/webrepl_cfg.py

holgerkenn/TheButtonProject

18cfbb37773c05a24a960b87c8677ec26d3160d6

[ "MIT" ]

null

src/webrepl_cfg.py

holgerkenn/TheButtonProject

18cfbb37773c05a24a960b87c8677ec26d3160d6

[ "MIT" ]

null

src/webrepl_cfg.py

holgerkenn/TheButtonProject

18cfbb37773c05a24a960b87c8677ec26d3160d6

[ "MIT" ]

null

PASS = 'iotbutton'

9.5

18

0.684211

2

19

6.5

1

0

0.157895

19

1

19

0.8125

0

0.473684

0

1

0

false

1

0

1

0

null

0

1

0

null

0

1

0

4

b621d2763dcf2b9a7d363aaab3dc03bc9168f3c7

610

py

Python

tksugar/widgets/__init__.py

TakamiChie/TkSugar

417af2abef48fa09e7f52375855783fef8e73d56

[ "MIT" ]

2

2020-09-11T23:09:00.000Z

2021-05-07T12:09:07.000Z

tksugar/widgets/__init__.py

TakamiChie/TkSugar

417af2abef48fa09e7f52375855783fef8e73d56

[ "MIT" ]

7

2020-11-17T09:55:36.000Z

2021-07-18T14:11:11.000Z

tksugar/widgets/__init__.py

TakamiChie/TkSugar

417af2abef48fa09e7f52375855783fef8e73d56

[ "MIT" ]

null

""" Widgets that require Generator-specific custom processing are stored in this package. For example, widgets such as tkinter.ttk.Notebook that do not display child elements on the GUI just by referencing them with the master argument of child elements are recorded here. This package is referenced with the highest priority when the Generator is executed. Therefore, even if there is a widget with the same name in another module, this module will be called. """ from tksugar.widgets.generatorsupport import GeneratorSupport from tksugar.widgets.notebook import Notebook from tksugar.widgets.menu import Menu

67.777778

182

0.82459

93

610

5.408602

0.655914

0.04175

0.107356

0

0.139344

610

9

183

67.777778

0.958095

0.747541

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

b6277b938a36af4b7c3b50f0df4a04586b3c1790

102

py

Python

fun_zone/other_fun/other_fun.py

viktor40/HammerBotPython

84b3cbc8fbba05666d81b442078e2281a1e766b1

[ "MIT" ]

3

2020-10-29T15:15:55.000Z

2020-10-29T21:42:58.000Z

fun_zone/other_fun/other_fun.py

viktor40/HammerBotPython

84b3cbc8fbba05666d81b442078e2281a1e766b1

[ "MIT" ]

null

fun_zone/other_fun/other_fun.py

viktor40/HammerBotPython

84b3cbc8fbba05666d81b442078e2281a1e766b1

[ "MIT" ]

2

2020-07-14T13:42:47.000Z

2020-10-25T16:42:09.000Z

from discord.ext import commands class OtherFun(commands.Cog): def __init__(self): pass

14.571429

32

0.696078

13

102

5.153846

0.923077

0

0.22549

102

6

33

17

0.848101

0

1

0.25

false

0.25

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

4

b63998a75660414b1a8bc687d44fa83ebb0a0d08

40,516

py

Python

code_examples/popart/block_sparse/examples/test_block_sparse.py

payoto/graphcore_examples

46d2b7687b829778369fc6328170a7b14761e5c6

[ "MIT" ]

260

2019-11-18T01:50:00.000Z

2022-03-28T23:08:53.000Z

code_examples/popart/block_sparse/examples/test_block_sparse.py

payoto/graphcore_examples

46d2b7687b829778369fc6328170a7b14761e5c6

[ "MIT" ]

27

2020-01-28T23:07:50.000Z

2022-02-14T15:37:06.000Z

code_examples/popart/block_sparse/examples/test_block_sparse.py

payoto/graphcore_examples

46d2b7687b829778369fc6328170a7b14761e5c6

[ "MIT" ]

56

2019-11-18T02:13:12.000Z

2022-02-28T14:36:09.000Z

# Copyright (c) 2020 Graphcore Ltd. All rights reserved. import os import numpy as np from functools import reduce from operator import mul import popart import pytest # range for filling blocks MATRIX_LOW_VALUE = -10 MATRIX_HIGH_VALUE = 10 # library provides support for 3 kinds of sparse MM's # from set of 2 inputs and one output, 2 of them will be dense # and the third will be sparse g_sparseMatMulTypeLookup = { 'DENSE_LHS_SPARSE_RHS_DENSE_OUT': 0, 'DENSE_LHS_DENSE_RHS_SPARSE_OUT': 1, 'SPARSE_LHS_SPARSE_RHS_SPARSE_OUT': 2 } # g_ -> global # g_input_data_type = "float32" g_output_data_type = "float32" g_pp_data_type = "float32" np.set_printoptions(linewidth=500) g_random_sparse_mask = np.random.RandomState() g_random_data = np.random.RandomState() g_random_labels = np.random.RandomState() """ Set seeds of random generatorts. """ g_random_sparse_mask.seed(1) g_random_data.seed(1) g_random_labels.seed(1) def create_sparse_list(dims, block_size, sparsity, initial_value=0): """ dims: dimensions of the sparse matrix block_size: size of a block (8x8, 16x16 etc) sparsity: sparsity level (0.4 means 40% of blocks are empty) returns-- block_sparse_matrix: np.array of num_blocks * block_sz dense_matrix: np.array if size dim with a dense representation of the matrix. i.e. explcit zeros for a zero block. Used to perform dense MM's for a reference output mask: list with sparsity pattern. size = num_blocks (both dense and sparse) e.g for a sparse matrix of size (6, 6) with block size 2x2 Matrix contains 9 blocks of size 2x2, some sparse and some dense If the 6x6 matrices has 2 non zero blocks, then .. Inputs: dims = [6, 6] block_size = [2,2] sparsity = 0.4 (say) Outputs: block_sparse_matrix = 2 x 4 array dense_matrix = 6x6 array sparsity = 9x1 list """ block_size_row = block_size[0] block_size_col = block_size[1] num_block_rows = dims[0] // block_size_row num_block_cols = dims[1] // block_size_col assert(sparsity < 1.0) proportion = [sparsity, 1 - sparsity] mask = g_random_sparse_mask.choice([0, 1], size=(num_block_rows, num_block_cols), p=proportion) # dont want mask to be all zeros while np.all(mask == 0): mask = g_random_sparse_mask.choice([0, 1], size=(num_block_rows, num_block_cols), p=proportion) if initial_value == 0: dense_matrix = np.zeros((num_block_rows * block_size_row, num_block_cols * block_size_col)) else: dense_matrix = np.empty((num_block_rows * block_size_row, num_block_cols * block_size_col)) dense_matrix.fill(initial_value) block_sparse_matrix = [] for block_row in range(num_block_rows): for block_col in range(num_block_cols): if mask[block_row][block_col]: block_data = g_random_data.randint(low=MATRIX_LOW_VALUE, high=MATRIX_HIGH_VALUE, size=block_size_row * block_size_col).astype("float32") block_sparse_matrix.append(block_data) dense_matrix[block_row * block_size_row: (block_row+1) * block_size_row, block_col * block_size_col: (block_col+1) * block_size_col] = block_data.reshape(block_size_row, block_size_col) # At this point mask is a 2D array, flatten it into 1D list and return, bsr_rhs is already a list (so convert to array) return np.array(block_sparse_matrix), dense_matrix, mask.flatten().tolist() def create_dense_matrix(dims): return g_random_data.randint(low=MATRIX_LOW_VALUE, high=MATRIX_HIGH_VALUE, size=dims).astype(g_input_data_type) def create_sparse_matrix(nominal_shape, block_size, sparsity, initial_value=0): """ Create a sparse_matrix. Inputs: nominal_shape: List of dimensions of the sparse tensor e.g (2, 3, 4, 4) block_size : size of each block (e.g. [8, 8, 8]) sparsity : block sparsity level (0.4 means, 40% of blocks are zeros) Outputs: bsr : sparse representation of matrix (nnz_blocks * block size) lengths_per_2d_plane: List with num-non-zero blocks per group dim. i.e. for a (2, 3, 4, 4) tensor with 2 nnz_blocks in each 4x4 matrix, this will have shape of 6x1 and each row storing 2 dense_matrix: dense representation of the matrix (for ref calc) mask : list of num_blocks (1 for non-zero blocks and 0 for others) """ # skip last two dimensions # last 2 dims enter the MM, others form the group num_grouped_dims = reduce(mul, nominal_shape[:-2], 1) rows = nominal_shape[-2] cols = nominal_shape[-1] # Create dense matrix of nominal dims if initial_value == 0: dense_matrix = np.zeros(nominal_shape).astype(g_input_data_type) else: dense_matrix = np.empty(nominal_shape).astype(g_input_data_type) dense_matrix.fill(initial_value) dense_matrix = dense_matrix.reshape((num_grouped_dims, rows, cols)) dims = [nominal_shape[-2], nominal_shape[-1]] bsr = [] bsr_lengths_per_2d_plane = [] mask = [] for dim in range(num_grouped_dims): _bsr, dense_matrix[dim], _mask = create_sparse_list(dims, block_size, sparsity, initial_value) # _bsr comes as array # _mask comes as list bsr.extend(_bsr) mask.extend(_mask) bsr_lengths_per_2d_plane.append(_bsr.shape[0]) dense_matrix = dense_matrix.reshape(nominal_shape) mask = np.array(mask) block_size_row = block_size[0] block_size_col = block_size[1] num_block_rows = dims[0] // block_size_row num_block_cols = dims[1] // block_size_col # all parameters are returned as numpy arrays return np.array(bsr), np.array(bsr_lengths_per_2d_plane), dense_matrix, mask def mm(lhs, rhs): return np.matmul(lhs, rhs) # Stable softmax numpy implementation def softmax(x): x_max = np.max(x, axis = -1) x = x - np.expand_dims(x_max, axis=-1) x = np.exp(x) x_sum = np.sum(x, axis=-1) x = x / np.expand_dims(x_sum, axis=-1) return x def sparse_mm_infer(sparse_mm_type, lhs_dims, vanilla_rhs_dims, block_size, sparsity_level, transpose_rhs, memory_cycle_ratio, inner_group_size): """ """ if transpose_rhs: matmul_dims = [lhs_dims[-2], vanilla_rhs_dims[-1], vanilla_rhs_dims[-2]] else: matmul_dims = [lhs_dims[-2], vanilla_rhs_dims[-2], vanilla_rhs_dims[-1]] lhs = create_dense_matrix(lhs_dims) if sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT']: bsr_rhs, lengths_per_2d_plane, vanilla_rhs, sparsity_mask = create_sparse_matrix(vanilla_rhs_dims, block_size[1:], sparsity_level) rhs = bsr_rhs rhs_dims = bsr_rhs.shape elif sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT']: output_dims = lhs_dims[:-1] output_dims.append(vanilla_rhs_dims[-1]) output_block_size = [block_size[0], block_size[2]] bsr_output, lengths_per_2d_plane, _, sparsity_mask = create_sparse_matrix(output_dims, output_block_size, sparsity_level) rhs_dims = vanilla_rhs_dims rhs = create_dense_matrix(rhs_dims) # Create a builder and construct a graph builder = popart.Builder() lhs_tensorInfo = popart.TensorInfo("FLOAT", lhs_dims) rhs_tensorInfo = popart.TensorInfo("FLOAT", rhs_dims) lhsTensor = builder.addInputTensor(lhs_tensorInfo) rhsTensor = builder.addInputTensor(rhs_tensorInfo) outTensor = builder.customOp(opName = "BSMatMul", opVersion=1, domain = "ai.graphcore", inputs = [lhsTensor, rhsTensor], attributes = { "bsr_rhs_lengths_per_2d_plane": lengths_per_2d_plane.tolist(), "matrix_dims": matmul_dims, "block_size": block_size, "sparsity_mask": sparsity_mask.tolist(), "bsmatmul_type": sparse_mm_type, "transpose_rhs": transpose_rhs, "memory_cycle_ratio": memory_cycle_ratio, "inner_group_size": inner_group_size, "in_type": g_input_data_type, "out_type": g_output_data_type, "pp_type": g_pp_data_type })[0] builder.addOutputTensor(outTensor) proto = builder.getModelProto() # Describe how to run the model dataFlow = popart.DataFlow(1, {outTensor: popart.AnchorReturnType("ALL")}) # Create a session to compile and execute the graph session = popart.InferenceSession( fnModel=proto, dataFlow=dataFlow, deviceInfo=popart.DeviceManager().acquireAvailableDevice(1)) # Compile graph session.prepareDevice() # Create buffers to receive results from the execution anchors = session.initAnchorArrays() rhs = np.array(rhs, dtype=g_input_data_type) stepio = popart.PyStepIO({lhsTensor: lhs, rhsTensor: rhs}, anchors) session.run(stepio) ipuOutput = anchors[outTensor] if sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT']: if transpose_rhs: transpose_indices = list(range(len(vanilla_rhs_dims))) transpose_indices[-2], transpose_indices[-1] = transpose_indices[-1], transpose_indices[-2] vanilla_rhs = vanilla_rhs.transpose(tuple(transpose_indices)) goldOutput = mm(lhs, vanilla_rhs) else: goldOutput = mm(lhs, vanilla_rhs) else: assert len(lhs.shape) == len(rhs.shape) if(len(lhs.shape) == 2): lhs = np.expand_dims(lhs, 0) rhs = np.expand_dims(rhs, 0) mmOutput = mm(lhs, rhs) totalGroupDims = int(np.prod(lhs_dims[:-2])) num_rows_sparsity_mask_2d = output_dims[-2] // block_size[0] num_cols_sparsity_mask_2d = output_dims[-1] // block_size[2] assert sparsity_mask.shape == (totalGroupDims * num_rows_sparsity_mask_2d * num_cols_sparsity_mask_2d,) mmOutput = mmOutput.reshape((totalGroupDims, lhs_dims[-2], rhs_dims[-1])) goldOutput = [] for dim in range(totalGroupDims): offset = num_rows_sparsity_mask_2d * num_cols_sparsity_mask_2d mmOutput_2d = mmOutput[dim] sliced_sparsity_mask = sparsity_mask[dim * offset: dim * offset + offset] for sparsity_mask_idx in range(len(sliced_sparsity_mask)): if sliced_sparsity_mask[sparsity_mask_idx]: mmOutput_2d_row_start = (sparsity_mask_idx // num_cols_sparsity_mask_2d) * block_size[0] mmOutput_2d_row_end = mmOutput_2d_row_start + block_size[0] mmOutput_2d_col_start = (sparsity_mask_idx % num_cols_sparsity_mask_2d) * block_size[2] mmOutput_2d_col_end = mmOutput_2d_col_start + block_size[2] mmOutput_2d_sliced = mmOutput_2d[mmOutput_2d_row_start: mmOutput_2d_row_end, mmOutput_2d_col_start: mmOutput_2d_col_end] goldOutput.append(mmOutput_2d_sliced.reshape(block_size[0] * block_size[2])) goldOutput = np.array(goldOutput) return ipuOutput, goldOutput def sparse_mm_train(sparse_mm_type, lhs_dims, vanilla_rhs_dims, block_size, sparsity_level, transpose_rhs, memory_cycle_ratio, inner_group_size): if transpose_rhs: matmul_dims = [lhs_dims[-2], vanilla_rhs_dims[-1], vanilla_rhs_dims[-2]] else: matmul_dims = [lhs_dims[-2], vanilla_rhs_dims[-2], vanilla_rhs_dims[-1]] lhs = create_dense_matrix(lhs_dims) if sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT']: bsr_rhs, lengths_per_2d_plane, vanilla_rhs, sparsity_mask = create_sparse_matrix(vanilla_rhs_dims, block_size[1:], sparsity_level) rhs = bsr_rhs rhs_dims = bsr_rhs.shape elif sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT']: output_dims = lhs_dims[:-1] output_dims.append(vanilla_rhs_dims[-1]) output_block_size = [block_size[0], block_size[2]] bsr_output, lengths_per_2d_plane, vanilla_output, sparsity_mask = create_sparse_matrix(output_dims, output_block_size, sparsity_level) lhs_inv = np.linalg.inv(lhs) rhs = np.matmul(lhs_inv, vanilla_output) rhs_dims = vanilla_rhs_dims # MODEL CREATION builder = popart.Builder() lhs_tensorInfo = popart.TensorInfo("FLOAT", lhs_dims) lhsTensor = builder.addInputTensor(lhs_tensorInfo) rhsTensor = builder.addInitializedInputTensor(rhs) outTensor = builder.customOp(opName = "BSMatMul", opVersion=1, domain = "ai.graphcore", inputs = [lhsTensor, rhsTensor], attributes = { "bsr_rhs_lengths_per_2d_plane": lengths_per_2d_plane.tolist(), "matrix_dims": matmul_dims, "block_size": block_size, "sparsity_mask": sparsity_mask.tolist(), "bsmatmul_type": sparse_mm_type, "transpose_rhs": transpose_rhs, "memory_cycle_ratio": memory_cycle_ratio, "inner_group_size": inner_group_size, "in_type": g_input_data_type, "out_type": g_output_data_type, "pp_type": g_pp_data_type })[0] builder.addOutputTensor(outTensor) probs = builder.aiOnnx.softmax([outTensor], axis=1) if sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT']: labels_shape = lhs_dims[:-1] elif sparse_mm_type == g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT']: labels_shape = [np.sum(sparsity_mask)] label_tensorInfo = popart.TensorInfo("INT32", labels_shape) labelTensor = builder.addInputTensor(label_tensorInfo) loss = builder.aiGraphcore.nllloss([probs, labelTensor], debugContext = "nllLossVal") proto = builder.getModelProto() ####################### # Describe how to run the model anchor_desc = { outTensor: popart.AnchorReturnType("ALL"), loss: popart.AnchorReturnType("ALL") } dataFlow = popart.DataFlow(1, anchor_desc) label_data = g_random_labels.choice(9, labels_shape) session = popart.TrainingSession(fnModel=proto, loss=loss, deviceInfo=popart.DeviceManager().acquireAvailableDevice(1), optimizer=popart.ConstSGD(0.01), dataFlow=dataFlow) # Compile graph session.prepareDevice() # Create buffers to receive results from the execution anchors = session.initAnchorArrays() # TRAINING session.weightsFromHost() stepio = popart.PyStepIO({ lhsTensor: lhs, labelTensor: label_data}, anchors) session.run(stepio) def sparse_softmax(dims, block_size, sparsity_level, inner_group_size): """ """ sparse_input, lengths_per_2d_plane, dense_input, sparsity_mask = create_sparse_matrix(dims, block_size, sparsity_level, -1000) # Create a builder and construct a graph builder = popart.Builder() tensor_info = popart.TensorInfo("FLOAT", sparse_input.shape) input_tensor = builder.addInputTensor(tensor_info) output_tensor = builder.customOp(opName = "BsSoftmax", opVersion = 1, domain = "ai.graphcore", inputs = [input_tensor], attributes = { "matrixDims": dims, "blockSize": block_size, "sparsity": sparsity_mask.tolist(), "groupSizes": lengths_per_2d_plane.tolist(), "innerGroupSize": inner_group_size, "subBlockMaskPerGroup": "None" * len(lengths_per_2d_plane) })[0] builder.addOutputTensor(output_tensor) proto = builder.getModelProto() # Describe how to run the model dataFlow = popart.DataFlow(1, {output_tensor: popart.AnchorReturnType("ALL")}) # Create a session to compile and execute the graph session = popart.InferenceSession( fnModel=proto, dataFlow=dataFlow, deviceInfo=popart.DeviceManager().acquireAvailableDevice(1)) # Compile graph session.prepareDevice() # Create buffers to receive results from the execution anchors = session.initAnchorArrays() sparse_input = np.array(sparse_input, dtype=g_input_data_type) stepio = popart.PyStepIO({input_tensor: sparse_input}, anchors) session.run(stepio) ipu_output = anchors[output_tensor] group_dims = dims[:-2] mat_dims = dims[-2:] blocks_2d = [mat_dims[0] // block_size[0], mat_dims[1] // block_size[1]] num_blocks_2d = blocks_2d[0] * blocks_2d[1] block_area = block_size[0] * block_size[1] total_group_dims = int(np.prod(group_dims)) assert sparsity_mask.shape == (total_group_dims * num_blocks_2d,) cpu_output = softmax(dense_input) np.set_printoptions(precision=2) np.set_printoptions(suppress=True) cpu_output = cpu_output.reshape([total_group_dims, blocks_2d[0], block_size[0], blocks_2d[1], block_size[1]]) cpu_output = np.transpose(cpu_output, [0, 1, 3, 2, 4]) cpu_output = cpu_output.reshape(total_group_dims, num_blocks_2d, block_area) gold_output = [] offset = 0 for g in range(total_group_dims): cpu_output_2d = cpu_output[g] sliced_sparsity_mask = sparsity_mask[offset: offset + num_blocks_2d] offset = offset + num_blocks_2d for sparsity_mask_idx in range(num_blocks_2d): if sliced_sparsity_mask[sparsity_mask_idx]: gold_output.append(cpu_output_2d[sparsity_mask_idx]) gold_output = np.array(gold_output) assert ipu_output.shape == gold_output.shape return ipu_output, gold_output # # INFERENCE TEST # # test_data_infer tuple --> (matMulType, lhs_dims, rhs_dims, block_size, sparsity, transpose_rhs, inner_group_size) test_data_infer = [ # 2D ("tag_inf_0", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [8, 8], [8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_1", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [16, 16], [16, 16], [8, 8, 8], 0.1, False, 1), ("tag_inf_2", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [32, 32], [32, 32], [16, 8, 8], 0.8, False, 1), ("tag_inf_3", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [64, 64], [64, 256], [64, 8, 64], 0.9, False, 1), ("tag_inf_4", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [128, 128], [128, 128], [32, 8, 16], 0.2, False, 1), # 3D, False ("tag_inf_5", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [2, 8, 8], [2, 8, 8], [8, 8, 8], 0.1, False, 1), ("tag_inf_6", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [5, 16, 16], [5, 16, 16], [8, 8, 8], 0.3, False, 1), ("tag_inf_7", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [7, 32, 32], [7, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_8", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [11, 64, 64], [11, 64, 64], [64, 8, 64], 0.6, False, 1), ("tag_inf_9", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [12, 128, 128], [12, 128, 128], [32, 8, 16], 0.8, False, 1), # 4D, False ("tag_inf_10", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 8, 8], [1, 1, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_11", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 16, 16], [1, 1, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_inf_12", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 32, 32], [1, 1, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_13", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 64, 128], [1, 1, 128, 256], [64, 8, 64], 0.5, False, 1), ("tag_inf_14", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 128, 64], [1, 1, 64, 128], [32, 8, 16], 0.5, False, 1), ("tag_inf_14", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 2, 8, 8], [1, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_16", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 5, 16, 16], [1, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_inf_17", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 7, 32, 32], [1, 7, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_18", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 5, 64, 128], [1, 5, 128, 256], [64, 8, 64], 0.5, False, 1), ("tag_inf_19", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 12, 128, 64], [1, 12, 64, 128], [32, 8, 16], 0.5, False, 1), ("tag_inf_20", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [2, 2, 8, 8], [2, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_21", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [5, 5, 16, 16], [5, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_inf_22", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [13, 7, 32, 32], [13, 7, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_24", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 12, 128, 64], [1, 12, 64, 128], [32, 8, 16], 0.5, False, 1), # 2D, lhs has to be square to take inverse, False ("tag_inf_25", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [8, 8], [8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_26", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [16, 16], [16, 16], [8, 8, 8], 0.1, False, 1), ("tag_inf_27", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [32, 32], [32, 32], [16, 8, 8], 0.8, False, 1), ("tag_inf_28", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [64, 64], [64, 64], [64, 8, 64], 0.9, False, 1), ("tag_inf_29", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [128, 128], [128, 128], [32, 8, 16], 0.7, False, 1), # 3D, lhs has to be square to take, False ("tag_inf_30", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [2, 8, 8], [2, 8, 8], [8, 8, 8], 0.1, False, 1), ("tag_inf_31", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [5, 16, 16], [5, 16, 16], [8, 8, 8], 0.3, False, 1), ("tag_inf_32", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [7, 32, 32], [7, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_33", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [11, 64, 64], [11, 64, 64], [64, 8, 64], 0.6, False, 1), ("tag_inf_34", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [12, 128, 128], [12, 128, 128], [32, 8, 16], 0.1, False, 1), # 4D, lhs has to be square to take, False ("tag_inf_36", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 8, 8], [1, 1, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_36", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 16, 16], [1, 1, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_inf_37", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 32, 32], [1, 1, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_38", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 64, 64], [1, 1, 64, 256], [64, 8, 64], 0.5, False, 1), ("tag_inf_39", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 128, 128], [1, 1, 128, 128], [32, 8, 16], 0.5, False, 1), ("tag_inf_40", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 2, 8, 8], [1, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_41", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 5, 16, 16], [1, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_inf_42", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 7, 32, 32], [1, 7, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_43", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 11, 64, 64], [1, 11, 64, 256], [64, 8, 64], 0.5, False, 1), ("tag_inf_44", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 12, 128, 128], [1, 12, 128, 128], [32, 8, 16], 0.5, False, 1), ("tag_inf_45", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [2, 2, 8, 8], [2, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_inf_46", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [5, 5, 16, 16], [5, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_inf_47", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [13, 7, 32, 32], [13, 7, 32, 32], [16, 8, 8], 0.5, False, 1), ("tag_inf_49", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 12, 128, 128], [1, 12, 128, 1024], [32, 8, 16], 0.5, False, 1), # For transpose_rhs True case, last 2 dimensions of block_size must be 8 ("tag_inf_50", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [8, 8], [8, 8], [8, 8, 8], 0.5, True, 1), ("tag_inf_51", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [16, 16], [16, 16], [8, 8, 8], 0.1, True, 1), ("tag_inf_52", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [32, 32], [32, 32], [16, 8, 8], 0.8, True, 1), ("tag_inf_53", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [64, 64], [256, 64], [64, 8, 8], 0.9, True, 1), ("tag_inf_54", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [128, 128], [128, 128], [32, 8, 8], 0.2, True, 1), ("tag_inf_55", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [2, 8, 8], [2, 8, 8], [8, 8, 8], 0.5, True, 1), ("tag_inf_56", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [3, 16, 16], [3, 16, 16], [8, 8, 8], 0.1, True, 1), ("tag_inf_57", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [7, 128, 128], [7, 128, 128], [32, 8, 8], 0.2, True, 1), ("tag_inf_58", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [3, 5, 8, 8], [3, 5, 8, 8], [8, 8, 8], 0.5, True, 1), ("tag_inf_59", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 6, 16, 16], [1, 6, 16, 16], [8, 8, 8], 0.1, True, 1), ("tag_inf_60", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [4, 4, 32, 32], [4, 4, 32, 32], [16, 8, 8], 0.8, True, 1), # 3D, inner group size > 1 ("tag_inf_61", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [12, 128, 128], [12, 128, 128], [32, 8, 16], 0.8, False, 3), ("tag_inf_62", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [12, 128, 128], [12, 128, 128], [32, 8, 16], 0.1, False, 4), # 4D, inner group size > 1 ("tag_inf_23", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [4, 8, 64, 128], [4, 8, 128, 256], [64, 8, 64], 0.5, False, 4), ("tag_inf_48", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [3, 11, 64, 64], [3, 11, 64, 256], [64, 8, 64], 0.5, False, 3), ] @pytest.mark.parametrize("tag, matmul_type, lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, inner_group_size", test_data_infer) def test_bsmatmul_infer(custom_ops, tag, matmul_type, lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, inner_group_size): print("Running test_bsmatmul_infer() with tag: {}, matmul_type:{}, lhs_dims:{}, rhs_dims:{}, block_size:{}, sparsity_level:{}, transpose_rhs:{}, inner_group_size {}" .format(tag, "DENSE_LHS_SPARSE_RHS_DENSE_OUT" if matmul_type == g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'] else "DENSE_LHS_DENSE_RHS_SPARSE_OUT", lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, inner_group_size)) memory_cycle_ratio = 1.0 ipuOutput, goldOutput = sparse_mm_infer(matmul_type, lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, memory_cycle_ratio, inner_group_size) rtol = 1e-3 atol = 1e-3 np.testing.assert_allclose(ipuOutput, goldOutput, rtol=rtol, atol=atol) # # TRAINING TEST # # test_data_train tuple --> (matMulType, lhs_dims, rhs_dims, block_size, sparsity, transpose_rhs, inner_group_size) test_data_train = [ # 2D ("tag_tr_0", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [8, 8], [8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_1", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [16, 16], [16, 16], [8, 8, 8], 0.1, False, 1), ("tag_tr_2", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [32, 32], [32, 32], [8, 8, 8], 0.8, False, 1), ("tag_tr_3", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [64, 64], [64, 256], [8, 8, 8], 0.9, False, 1), ("tag_tr_4", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [128, 128], [128, 128], [8, 8, 8], 0.2, False, 1), # 3D, ("tag_tr_5", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [2, 16, 16], [2, 16, 16], [8, 8, 8], 0.1, False, 1), ("tag_tr_6", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [5, 16, 16], [5, 16, 16], [8, 8, 8], 0.3, False, 1), ("tag_tr_7", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [7, 32, 32], [7, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_8", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [11, 64, 64], [11, 64, 64], [8, 8, 8], 0.6, False, 1), ("tag_tr_9", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [12, 128, 128], [12, 128, 128], [8, 8, 8], 0.8, False, 1), # 4D, ("tag_tr_10", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 8, 8], [1, 1, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_11", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 16, 16], [1, 1, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_tr_12", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 32, 32], [1, 1, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_13", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 64, 128], [1, 1, 128, 256], [8, 8, 8], 0.5, False, 1), ("tag_tr_14", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 1, 128, 64], [1, 1, 64, 128], [8, 8, 8], 0.5, False, 1), ("tag_tr_15", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 2, 8, 8], [1, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_16", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 5, 16, 16], [1, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_tr_17", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 7, 32, 32], [1, 7, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_18", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 11, 64, 128], [1, 11, 128, 256], [8, 8, 8], 0.5, False, 1), ("tag_tr_19", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 12, 128, 64], [1, 12, 64, 128], [8, 8, 8], 0.5, False, 1), ("tag_tr_20", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [2, 2, 8, 8], [2, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_21", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [5, 5, 16, 16], [5, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_tr_22", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [13, 7, 32, 32], [13, 7, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_23", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [3, 11, 64, 128], [3, 11, 128, 256], [8, 8, 8], 0.5, False, 1), ("tag_tr_24", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 12, 128, 64], [1, 12, 64, 128], [8, 8, 8], 0.5, False, 1), # 2D, lhs has to be square to take inverse ("tag_tr_25", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [8, 8], [8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_26", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [16, 16], [16, 16], [8, 8, 8], 0.1, False, 1), ("tag_tr_27", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [32, 32], [32, 32], [8, 8, 8], 0.8, False, 1), ("tag_tr_28", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [64, 64], [64, 256], [8, 8, 8], 0.9, False, 1), ("tag_tr_29", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [128, 128], [128, 128], [8, 8, 8], 0.2, False, 1), # 3D, lhs has to be square to take ("tag_tr_30", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [2, 8, 8], [2, 8, 8], [8, 8, 8], 0.1, False, 1), ("tag_tr_31", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [5, 16, 16], [5, 16, 16], [8, 8, 8], 0.3, False, 1), ("tag_tr_32", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [7, 32, 32], [7, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_33", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [11, 64, 64], [11, 64, 64], [8, 8, 8], 0.6, False, 1), ("tag_tr_34", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [12, 128, 128], [12, 128, 128], [8, 8, 8], 0.3, False, 1), # 4D, lhs has to be square to take ("tag_tr_35", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 8, 8], [1, 1, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_36", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 16, 16], [1, 1, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_tr_37", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 32, 32], [1, 1, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_38", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 64, 64], [1, 1, 64, 256], [8, 8, 8], 0.5, False, 1), ("tag_tr_39", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 1, 128, 128], [1, 1, 128, 128], [8, 8, 8], 0.5, False, 1), ("tag_tr_40", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 2, 8, 8], [1, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_41", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 5, 16, 16], [1, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_tr_42", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 7, 32, 32], [1, 7, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_43", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 11, 64, 64], [1, 11, 64, 256], [8, 8, 8], 0.5, False, 1), ("tag_tr_44", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 12, 128, 128], [1, 12, 128, 128], [8, 8, 8], 0.5, False, 1), ("tag_tr_45", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [2, 2, 8, 8], [2, 2, 8, 8], [8, 8, 8], 0.5, False, 1), ("tag_tr_46", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [5, 5, 16, 16], [5, 5, 16, 16], [8, 8, 8], 0.8, False, 1), ("tag_tr_47", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [13, 7, 32, 32], [13, 7, 32, 32], [8, 8, 8], 0.5, False, 1), ("tag_tr_48", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [3, 11, 64, 64], [3, 11, 64, 256], [8, 8, 8], 0.5, False, 1), ("tag_tr_49", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [1, 12, 128, 128], [1, 12, 128, 1024], [8, 8, 8], 0.5, False, 1), # For transpose_rhs True case, last 2 dimensions of block_size must be 8 ("tag_tr_50", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [8, 8], [8, 8], [8, 8, 8], 0.5, True, 1), ("tag_tr_51", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [16, 16], [16, 16], [8, 8, 8], 0.1, True, 1), ("tag_tr_52", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [32, 32], [32, 32], [8, 8, 8], 0.8, True, 1), ("tag_tr_53", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [64, 64], [256, 64], [8, 8, 8], 0.9, True, 1), ("tag_tr_54", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [128, 128], [128, 128], [8, 8, 8], 0.2, True, 1), ("tag_tr_55", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [2, 8, 8], [2, 8, 8], [8, 8, 8], 0.5, True, 1), ("tag_tr_56", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [3, 16, 16], [3, 16, 16], [8, 8, 8], 0.1, True, 1), ("tag_tr_57", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [7, 128, 128], [7, 128, 128], [8, 8, 8], 0.2, True, 1), ("tag_tr_58", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [3, 5, 8, 8], [3, 5, 8, 8], [8, 8, 8], 0.5, True, 1), ("tag_tr_59", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [1, 6, 16, 16], [1, 6, 16, 16], [8, 8, 8], 0.1, True, 1), ("tag_tr_60", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [4, 4, 32, 32], [4, 4, 32, 32], [8, 8, 8], 0.8, True, 1), # 3D, inner group size > 1 ("tag_tr_61", g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'], [12, 128, 128], [12, 128, 128], [8, 8, 8], 0.8, False, 3), ("tag_tr_62", g_sparseMatMulTypeLookup['DENSE_LHS_DENSE_RHS_SPARSE_OUT'], [12, 128, 128], [12, 128, 128], [8, 8, 8], 0.1, False, 4), ] @pytest.mark.parametrize("tag, matmul_type, lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, inner_group_size", test_data_train) def test_bsmatmul_train(custom_ops, tag, matmul_type, lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, inner_group_size): print("Running test_bsmatmul_train() with tag: {}, matmul_type:{}, lhs_dims:{}, rhs_dims:{}, block_size:{}, sparsity_level:{}, transpose_rhs:{}, inner_group_size {}" .format(tag, "DENSE_LHS_SPARSE_RHS_DENSE_OUT" if matmul_type == g_sparseMatMulTypeLookup['DENSE_LHS_SPARSE_RHS_DENSE_OUT'] else "DENSE_LHS_DENSE_RHS_SPARSE_OUT", lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, inner_group_size)) memory_cycle_ratio = 1.0 sparse_mm_train(matmul_type, lhs_dims, rhs_dims, block_size, sparsity_level, transpose_rhs, memory_cycle_ratio, inner_group_size) # test_data_softmax tuple --> (dims, block_size, sparsity, inner_group_size) test_data_softmax = [ # 2D ("tag_sm_0", [8, 8], [8, 8], 0.0, 1), # 3D ("tag_sm_1", [16, 16], [8, 8], 0.4, 1), # 4D ("tag_sm_2", [2, 2, 16, 16], [8, 8], 0.3, 1), # 5D, inner group size = 1 ("tag_sm_3", [2, 3, 2, 16, 16], [8, 8], 0.1, 1), # 5D, inner group size > 1 ("tag_sm_4", [2, 3, 2, 16, 16], [8, 8], 0.1, 0), ("tag_sm_5", [2, 3, 2, 16, 16], [8, 8], 0.1, 6), ] @pytest.mark.parametrize("tag, dims, block_size, sparsity_level, inner_group_size", test_data_softmax) def test_bs_softmax(custom_ops, tag, dims, block_size, sparsity_level, inner_group_size): print("Running test_bs_softmax() with tag: {}, dims:{}, block_size:{}, sparsity_level:{}, inner_group_size {}" .format(tag, dims, block_size, sparsity_level, inner_group_size)) ipu_output, gold_output = sparse_softmax(dims, block_size, sparsity_level, inner_group_size) np.testing.assert_allclose(ipu_output, gold_output, rtol=1e-2, atol=1e-2) if __name__ == "__main__": ipu_output, gold_output = sparse_softmax([2, 2, 16, 16], [8, 8], 0.3, 1) np.testing.assert_allclose(ipu_output, gold_output, rtol=1e-2, atol=1e-2)

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1

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4

b646e70957f42088d6111a5dc7519a69d0f4b90e

263

py

Python

divedownload.py

AmoghRRao/Game-Recommendation-System

c2abbd699fca22f863fa49c26fc42fd98a3d5177

[ "Apache-2.0" ]

null

divedownload.py

AmoghRRao/Game-Recommendation-System

c2abbd699fca22f863fa49c26fc42fd98a3d5177

[ "Apache-2.0" ]

null

divedownload.py

AmoghRRao/Game-Recommendation-System

c2abbd699fca22f863fa49c26fc42fd98a3d5177

[ "Apache-2.0" ]

null

from google_drive_downloader import GoogleDriveDownloader as gdd gdd.download_file_from_google_drive(file_id='14LXxwldPTV5K1EmrDr-HQc1svBhMKDvT', dest_path='./similarity.pkl', unzip=False)

37.571429

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0.623574

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0

0.027778

0.315589

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0.838889

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null

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1

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1

0

null

0

1

0

4

b686f562b278bea748b1a7f47ef4eebd0183debb

419

py

Python

DailyProgrammer/DP20150107W.py

DayGitH/Python-Challenges

bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf

[ "MIT" ]

2

2020-12-23T18:59:22.000Z

2021-04-14T13:16:09.000Z

DailyProgrammer/DP20150107W.py

DayGitH/Python-Challenges

bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf

[ "MIT" ]

null

DailyProgrammer/DP20150107W.py

DayGitH/Python-Challenges

bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf

[ "MIT" ]

null

""" [Weekly #19] Looking forward into 2015 - Predictions. https://www.reddit.com/r/dailyprogrammer/comments/2rfexe/weekly_19_looking_forward_into_2015_predictions/ As we enter the new year - What are some trends/predictions you see in computer science, software engineering, programming or related fields forth coming or happening for this new year? """ def main(): pass if __name__ == "__main__": main()

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b69c1b3771e1541308260da20d12a22f3aa1240d

27

py

Python

lang/Python/increment-a-numerical-string-1.py

ethansaxenian/RosettaDecode

8ea1a42a5f792280b50193ad47545d14ee371fb7

[ "MIT" ]

5

2021-01-29T20:08:05.000Z

2022-03-22T06:16:05.000Z

lang/Python/increment-a-numerical-string-1.py

ethansaxenian/RosettaDecode

8ea1a42a5f792280b50193ad47545d14ee371fb7

[ "MIT" ]

null

lang/Python/increment-a-numerical-string-1.py

ethansaxenian/RosettaDecode

8ea1a42a5f792280b50193ad47545d14ee371fb7

[ "MIT" ]

1

2018-11-09T22:08:40.000Z

next = str(int('123') + 1)

13.5

26

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27

2.8

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1

0

1

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null

0

4

fcb219589f7f6fae701c64ddba094835676e7327

3,153

py

Python

moniter/index.py

tjandy/work

f9179a6a8e87de4127ebef2f886818c149a32a59

[ "MIT" ]

null

moniter/index.py

tjandy/work

f9179a6a8e87de4127ebef2f886818c149a32a59

[ "MIT" ]

null

moniter/index.py

tjandy/work

f9179a6a8e87de4127ebef2f886818c149a32a59

[ "MIT" ]

null

import json from flask import Flask,request,render_template import os import time app = Flask(__name__) def getTime(timestr,interval): process = os.popen('cat data/'+timestr+'.log|grep date |awk \'{print $2}\'|sed \'s/$/,/g\'|awk \'{printf("%s",$0);}\'') data = process.read() process.close() return data def getServerMem(timestr,name,interval): process = os.popen('cat data/'+timestr+'.log|grep -w '+name+' |awk \'{print $3}\'|sed \'s/$/,/g\'|awk \'{printf("%s",$0);}\'') data = process.read() process.close() return data def getServerCpu(timestr,name,interval): process = os.popen('cat data/'+timestr+'.log|grep -w '+name+' |awk \'{print $2}\'|sed \'s/$/,/g\'|awk \'{printf("%s",$0);}\'') data = process.read() process.close() return data def getOnline(timestr): process = os.popen('tail -n7 data/'+timestr+'.log|grep online |awk \'{print $2}\'') data = process.read() process.close() return data def tojson(name,data): return {'name':name,'data':data} @app.route('/info.do',methods=['GET']) def GetInfo(): curtime=time.localtime() timestr = time.strftime("%Y-%m-%d", curtime) interval = time.strftime("%H:%M",curtime) tt = getTime(timestr,interval) cur = getOnline(timestr) name = ["mapserver","mapserver2","loginserver","baseserver","dbserver","connectserver"] mem=[] cpu=[] for index,value in enumerate(name): mem.append(getServerMem(timestr,value,interval)) for value in name: cpu.append(getServerCpu(timestr,value,interval)) memdata=[] for index,value in enumerate(name): memdata.append(tojson(value,mem[index])) cpudata=[] for index,value in enumerate(name): cpudata.append(tojson(value,cpu[index])) return render_template('mon.html',timedata=tt,online=cur,memdata=memdata,cpudata=cpudata) @app.route('/cpu.do',methods=['GET']) def GetCpuInfo(): curtime=time.localtime() timestr = time.strftime("%Y-%m-%d", curtime) interval = time.strftime("%H:%M",curtime) tt = getTime(timestr,interval) cur = getOnline(timestr) name = ["mapserver","mapserver2","loginserver","baseserver","dbserver","connectserver"] cpu=[] for value in name: cpu.append(getServerCpu(timestr,value,interval)) cpudata=[] for index,value in enumerate(name): cpudata.append(tojson(value,cpu[index])) return render_template('mon.html',timedata=tt,online=cur,cpudata=cpudata) @app.route('/mem.do',methods=['GET']) def GetMemInfo(): curtime=time.localtime() timestr = time.strftime("%Y-%m-%d", curtime) interval = time.strftime("%H:%M",curtime) tt = getTime(timestr,interval) cur = getOnline(timestr) name = ["mapserver","mapserver2","loginserver","baseserver","dbserver","connectserver"] mem=[] for value in name: mem.append(getServerMem(timestr,value,interval)) data=[] for index,value in enumerate(name): data.append(tojson(value,mem[index])) return render_template('mon.html',timedata=tt,online=cur,memdata=data) app.run(host='0.0.0.0',port=8888,debug=True)

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fcfd593d20dab4f4702c9ba9bc12d66859e22310

90

py

Python

quickumls/__init__.py

equipe22/QuickUMLS

950383385ab28cb1c0cd4a67a46ee3a49a4a501e

[ "MIT" ]

283

2016-07-21T10:22:33.000Z

2022-03-28T22:15:21.000Z

quickumls/__init__.py

equipe22/QuickUMLS

950383385ab28cb1c0cd4a67a46ee3a49a4a501e

[ "MIT" ]

65

2016-08-11T04:33:13.000Z

2022-03-22T18:40:08.000Z

quickumls/__init__.py

equipe22/QuickUMLS

950383385ab28cb1c0cd4a67a46ee3a49a4a501e

[ "MIT" ]

74

2017-10-14T04:37:05.000Z

2022-01-27T07:37:30.000Z

from .core import QuickUMLS from .client import get_quickumls_client from .about import *

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null

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1e26ea7e48eb165042de4428a92a508779072563

116

py

Python

settings.py

kavehkm/MiddleWareSystem

de5484d7fab6582904506dcf7db19ecfffcc8df7

[ "Apache-2.0" ]

null

settings.py

kavehkm/MiddleWareSystem

de5484d7fab6582904506dcf7db19ecfffcc8df7

[ "Apache-2.0" ]

null

settings.py

kavehkm/MiddleWareSystem

de5484d7fab6582904506dcf7db19ecfffcc8df7

[ "Apache-2.0" ]

null

MIDDLEWARES = ( 'middlewares.middle_a', 'middlewares.middle_b', 'middlewares.middle_c', 'middlewares.middle_d' )

19.333333

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null

0

4

1e3d891bf17ddc54a3059b850dc2489217abb579

164

py

Python

problem0325.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

problem0325.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

problem0325.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

########################### # # #325 Stone Game II - Project Euler # https://projecteuler.net/problem=325 # # Code by Kevin Marciniak # ###########################

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4

1e3df4f8080941db8b932d73b60ea38707fc8cc7

3,915

py

Python

resources/Wireshark/WiresharkDissectorFoo/test/suite_follow.py

joshis1/C_Programming

4a8003321251448a167bfca0b595c5eeab88608d

[ "MIT" ]

2

2020-09-11T05:51:42.000Z

2020-12-31T11:42:02.000Z

resources/Wireshark/WiresharkDissectorFoo/test/suite_follow.py

joshis1/C_Programming

4a8003321251448a167bfca0b595c5eeab88608d

[ "MIT" ]

null

resources/Wireshark/WiresharkDissectorFoo/test/suite_follow.py

joshis1/C_Programming

4a8003321251448a167bfca0b595c5eeab88608d

[ "MIT" ]

null

# # -*- coding: utf-8 -*- # Wireshark tests # # Copyright (c) 2018 Peter Wu <peter@lekensteyn.nl> # # SPDX-License-Identifier: GPL-2.0-or-later # '''Follow Stream tests''' import subprocesstest import fixtures @fixtures.mark_usefixtures('test_env') @fixtures.uses_fixtures class case_follow_tcp(subprocesstest.SubprocessTestCase): def test_follow_tcp_bad_conditions(self, cmd_tshark, capture_file): '''Checks whether Follow TCP correctly handles lots of edge cases.''' # Edge cases include: # 1. two sequential segments # 2. out-of-order (swapped two sequential segments) # 3. Bad overlap (second overlap with different data should be ignored) # 4. Ignore bad retransmitted data, but extend with remaining data. # 5. Check handling of overlapping data while fragments are incomplete # (out-of-order - cannot add fragments to stream) # 6. lost but acked segments # 7. lost 3/5 fragments, but acked # Not checked: lost and not acked (currently truncated, is that OK?) proc = self.assertRun((cmd_tshark, '-r', capture_file('tcp-badsegments.pcap'), '-qz', 'follow,tcp,hex,0', )) self.assertIn("""\ =================================================================== Follow: tcp,hex Filter: tcp.stream eq 0 Node 0: 10.0.0.1:32323 Node 1: 10.0.0.2:80 00000000 47 45 54 20 2f 20 48 54 54 50 2f 31 2e 31 0d 0a GET / HT TP/1.1.. 00000010 48 6f 73 74 3a 6c 6f 63 61 6c 68 6f 73 74 0d 0a Host:loc alhost.. 00000020 58 2d 53 77 61 70 70 65 64 3a 20 31 73 74 0d 0a X-Swappe d: 1st.. 00000030 58 2d 53 77 61 70 70 65 64 3a 20 32 6e 64 0d 0a X-Swappe d: 2nd.. 00000040 58 2d 4f 76 65 72 6c 61 70 2d 50 61 63 6b 65 74 X-Overla p-Packet 00000050 3a 20 65 78 74 72 61 20 64 61 74 61 2d 2d 0d 0a : extra data--.. 00000060 58 2d 4f 6f 4f 2d 4f 76 65 72 6c 61 70 3a 20 74 X-OoO-Ov erlap: t 00000070 68 69 73 20 69 73 20 64 65 6c 61 79 65 64 0d 0a his is d elayed.. 00000080 58 2d 4f 6f 4f 2d 4f 76 65 72 6c 61 70 32 3a 20 X-OoO-Ov erlap2: 00000090 73 65 63 6f 6e 64 20 64 65 6c 61 79 65 64 0d 0a second d elayed.. 000000A0 58 2d 4f 6f 4f 2d 4f 76 65 72 6c 61 70 33 3a 65 X-OoO-Ov erlap3:e 000000B0 78 74 65 6e 64 20 66 72 61 67 6d 65 6e 74 0d 0a xtend fr agment.. 000000C0 5b 33 32 20 62 79 74 65 73 20 6d 69 73 73 69 6e [32 byte s missin 000000D0 67 20 69 6e 20 63 61 70 74 75 72 65 20 66 69 6c g in cap ture fil 000000E0 65 5d 00 e]. 000000E3 58 2d 4d 69 73 73 69 6e 67 2d 42 75 74 2d 41 63 X-Missin g-But-Ac 000000F3 6b 65 64 2d 50 72 65 76 69 6f 75 73 3a 31 0d 0a ked-Prev ious:1.. 00000103 5b 31 36 20 62 79 74 65 73 20 6d 69 73 73 69 6e [16 byte s missin 00000113 67 20 69 6e 20 63 61 70 74 75 72 65 20 66 69 6c g in cap ture fil 00000123 65 5d 00 e]. 00000126 3a : 00000127 5b 31 33 20 62 79 74 65 73 20 6d 69 73 73 69 6e [13 byte s missin 00000137 67 20 69 6e 20 63 61 70 74 75 72 65 20 66 69 6c g in cap ture fil 00000147 65 5d 00 e]. 0000014A 0d . 0000014B 5b 31 20 62 79 74 65 73 20 6d 69 73 73 69 6e 67 [1 bytes missing 0000015B 20 69 6e 20 63 61 70 74 75 72 65 20 66 69 6c 65 in capt ure file 0000016B 5d 00 ]. 0000016D 58 2d 4d 69 73 73 69 6e 67 2d 33 2d 4f 75 74 2d X-Missin g-3-Out- 0000017D 4f 66 2d 35 2d 42 75 74 2d 41 43 4b 3a 59 0d 0a Of-5-But -ACK:Y.. 0000018D 0d 0a .. =================================================================== """.replace("\r\n", "\n"), proc.stdout_str.replace("\r\n", "\n"))

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1

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null

0

4

1e6bb3c332ceba0fd537b955e1377973268d2f3a

137

py

Python

FlyHigh_Personal_Project_ParkSeHwan/once.py

MaengSanHa/flyhigh

461c8f7ce787b3961cdbcbc5c7c77a7ec45f7aeb

[ "Apache-2.0" ]

null

FlyHigh_Personal_Project_ParkSeHwan/once.py

MaengSanHa/flyhigh

461c8f7ce787b3961cdbcbc5c7c77a7ec45f7aeb

[ "Apache-2.0" ]

null

FlyHigh_Personal_Project_ParkSeHwan/once.py

MaengSanHa/flyhigh

461c8f7ce787b3961cdbcbc5c7c77a7ec45f7aeb

[ "Apache-2.0" ]

1

2019-10-18T06:52:37.000Z

import mw24 import nhis import safedriving if __name__ == "once": mw24.go_popup() nhis.once_go() safedriving.go()

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1ea7e1d0ef79c0ff756a9285244254eb9e3efcfe

71

py

Python

neurolib/models/bold/__init__.py

leonidas228/neurolib

a7aa6f487db73c3b64471007ac5a965da4a65f9a

[ "MIT" ]

258

2020-01-26T14:38:09.000Z

2022-03-31T14:54:04.000Z

neurolib/models/bold/__init__.py

leonidas228/neurolib

a7aa6f487db73c3b64471007ac5a965da4a65f9a

[ "MIT" ]

172

2020-01-27T11:02:28.000Z

2022-03-22T22:25:38.000Z

neurolib/models/bold/__init__.py

leonidas228/neurolib

a7aa6f487db73c3b64471007ac5a965da4a65f9a

[ "MIT" ]

49

2020-02-04T08:34:44.000Z

2022-03-28T09:29:12.000Z

from .model import BOLDModel from .timeIntegration import simulateBOLD

23.666667

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1eaf8b72c9dc1bb2c4f6f30372bed6e42a3ae2ab

116

py

Python

gems/forms.py

0xOddrey/DroppingGemsNFT

536c0c3f0f53ac9437d88625709609037306848e

[ "MIT" ]

null

gems/forms.py

0xOddrey/DroppingGemsNFT

536c0c3f0f53ac9437d88625709609037306848e

[ "MIT" ]

null

gems/forms.py

0xOddrey/DroppingGemsNFT

536c0c3f0f53ac9437d88625709609037306848e

[ "MIT" ]

null

from django import forms from .models import * class gemSearchForm(forms.Form): tokenId = forms.IntegerField()

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1ed00ee5a8f6c68165ca177e0725d198d84f82b6

345,403

py

Python

3algo/homo/5_3_7datap.py

allengrr/deadlock_project

933878077c45a7df04daa087407bb2620c064617

[ "MIT" ]

null

3algo/homo/5_3_7datap.py

allengrr/deadlock_project

933878077c45a7df04daa087407bb2620c064617

[ "MIT" ]

null

3algo/homo/5_3_7datap.py

allengrr/deadlock_project

933878077c45a7df04daa087407bb2620c064617

[ "MIT" ]

1

2021-03-21T17:54:26.000Z

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1.0, 1.1, 1.2, 2.4, 2.6, 1.2, 1.8, 1.8, 0.1, 0.2, 0.6, 0.3, 0.1, 4.7, 4.7, 0.4, 0.3, 0.7, 0.7, 1.0, 1.0, 0.8, 0.4, 1.4, 1.1, 1.1, 1.7, 1.0, 0.2, 1.2, 0.8, 1.3, 0.1, 1.0, 0.5, 0.8, 0.5, 0.6, 0.8, 1.2, 1.6, 1.1, 0.1, 1.1, 0.8, 0.7, 0.4, 0.5, 1.2, 0.6, 0.4, 0.1, 0.3, 0.8, 0.7, 0.4, 1.3, 1.2, 0.9, 0.5, 0.7, 0.1, 1.1, 0.3, 0.8, 0.4, 1.4, 1.1, 1.5, 0.6, 0.8, 2.1, 1.4, 1.4, 1.6, 1.7, 1.2, 0.4, 0.4, 1.4, 3.2, 3.7, 0.9, 0.0, 0.5, 0.3, 0.6, 0.5, 0.6, 0.1, 0.1, 0.2, 0.4, 0.0, 0.8, 0.1, 0.3, 0.8, 0.3, 0.4, 6.1, 7.2, 0.2, 0.7, 0.1, 0.1, 1.1, 0.0, 1.4, 0.0, 0.2, 5.6, 5.5, 1.9, 1.7, 1.5, 0.8, 2.1, 2.0, 0.8, 0.4, 2.2, 1.9, 0.3, 0.1, 0.6, 0.8, 4.3, 4.3, 1.4, 1.4, 0.1, 0.2, 1.9, 3.3, 0.7, 0.2, 1.1, 0.4, 0.6, 1.4, 1.5, 1.7, 1.2, 0.5, 1.4, 0.8, 1.7, 0.5, 0.2, 0.5, 0.5, 0.3, 0.7, 0.1, 0.9, 1.5, 0.4, 1.4, 0.4, 0.8, 1.3, 0.6, 1.6, 8.4, 6.4, 5.6, 4.9, 0.5, 0.3, 2.1, 2.4, 2.2, 0.3, 1.1, 2.4, 2.4, 2.7, 1.0, 2.3, 0.6, 3.1, 3.2, 1.1, 0.0, 0.2, 1.4, 3.1, 2.1, 0.0, 0.6, 0.3, 5.1, 3.2, 0.5, 1.4, 0.4, 0.2, 0.7, 1.0, 0.6, 0.5, 0.2, 2.0, 0.3, 0.6, 0.5, 1.1] off_mec5_3_7 = 242 off_cloud5_3_7 = 264 inward_mec5_3_7 = 180 loc5_3_7 = 763 deadlock5_3_7 = [6] memory5_3_7 = [0.2175, 0.218, 0.218, 0.2185, 0.2186, 0.2186, 0.2187, 0.2187, 0.2187, 0.2187, 0.2187, 0.2188, 0.2189, 0.2189, 0.2189, 0.219, 0.219, 0.219, 0.219, 0.219, 0.2191, 0.2191, 0.2191, 0.2192, 0.2192, 0.2192, 0.2193, 0.2193, 0.2193, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2196, 0.2196, 0.2196, 0.22, 0.2201, 0.2201, 0.2201, 0.2201, 0.2202, 0.2202, 0.2203, 0.2203, 0.2204, 0.2204, 0.2204, 0.2205, 0.2205, 0.2205, 0.2205, 0.2205, 0.2206, 0.2206, 0.2206, 0.2206, 0.2208, 0.2208, 0.2208, 0.2208, 0.2208, 0.2208, 0.2208, 0.2208, 0.2209, 0.2209, 0.2209, 0.2209, 0.2209, 0.221, 0.221, 0.221, 0.2211, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2212, 0.2213, 0.2213, 0.2213, 0.2213, 0.2214, 0.2214, 0.2215, 0.2215, 0.2215, 0.2215, 0.2217, 0.2217, 0.2218, 0.2218, 0.2218, 0.2218, 0.2218, 0.2219, 0.2219, 0.2221, 0.2221, 0.2221, 0.2222, 0.2222, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2224, 0.2224, 0.2224, 0.2225, 0.2225, 0.2225, 0.2225, 0.2225, 0.2225, 0.2227, 0.2228, 0.2229, 0.2229, 0.2229, 0.2229, 0.2229, 0.2229, 0.223, 0.223, 0.223, 0.223, 0.223, 0.223, 0.2231, 0.2231, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2234, 0.2234, 0.2235, 0.2235, 0.2235, 0.2235, 0.2235, 0.2235, 0.2236, 0.2236, 0.2236, 0.2236, 0.2236, 0.2236, 0.2237, 0.2237, 0.2238, 0.2238, 0.2238, 0.2238, 0.2238, 0.2238, 0.2238, 0.2238, 0.2239, 0.2239, 0.2239, 0.2239, 0.2239, 0.2239, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.2241, 0.2242, 0.2243, 0.2243, 0.2243, 0.2245, 0.2245, 0.2245, 0.2245, 0.2247, 0.2247, 0.2248, 0.2248, 0.2248, 0.2249, 0.2249, 0.2249, 0.2249, 0.2249, 0.2249, 0.2249, 0.2249, 0.2249, 0.2249, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.2251, 0.2252, 0.2252, 0.2252, 0.2252, 0.2252, 0.2252, 0.2253, 0.2253, 0.2253, 0.2253, 0.2253, 0.2253, 0.2254, 0.2254, 0.2254, 0.2254, 0.2254, 0.2254, 0.2254, 0.2254, 0.2255, 0.2255, 0.2255, 0.2255, 0.2255, 0.2256, 0.2256, 0.2256, 0.2256, 0.2256, 0.2256, 0.2256, 0.2257, 0.2257, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2258, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.226, 0.226, 0.226, 0.2262, 0.2263, 0.2263, 0.2263, 0.2263, 0.2263, 0.2263, 0.2263, 0.2264, 0.2265, 0.2265, 0.2265, 0.2265, 0.2265, 0.2265, 0.2265, 0.2265, 0.2266, 0.2266, 0.2266, 0.2266, 0.2266, 0.2266, 0.2266, 0.2266, 0.2266, 0.2266, 0.2267, 0.2267, 0.2267, 0.2268, 0.2268, 0.2268, 0.2268, 0.2268, 0.2268, 0.2268, 0.2268, 0.2268, 0.2269, 0.227, 0.227, 0.2271, 0.2271, 0.2275, 0.2278, 0.2278, 0.2279, 0.228, 0.228, 0.228, 0.228, 0.228, 0.228, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2281, 0.2282, 0.2282, 0.2282, 0.2282, 0.2282, 0.2283, 0.2283, 0.2283, 0.2283, 0.2283, 0.2283, 0.2283, 0.2283, 0.2285, 0.2285, 0.2285, 0.2285, 0.2286] task_received5_3_7 = 1269 sent_t5_3_7 = {'124': 471, '125': 396, '126': 402} cooperate5_3_7 = {'mec': 242, 'cloud': 264} task_record5_3_7 = {} outward_mec5_3_7 = 39 offload_check5_3_7 = [] timed_out_tasks5_3_7 = 0

20,317.823529

321,918

0.620924

87,268

345,403

2.457109

0.065706

0.001213

0.001492

0.000933

0.661521

0.323373

0.322777

0.104609

0.027012

0

0.710174

0.126363

345,403

17

321,919

20,317.823529

0.000421

0

0.00057

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false

0

null

0

1

0

1

0

null

0

4

94c2d3f1c8844f2f91cede88d7e526135be23826

95

py

Python

checkerapp/apps.py

sahilr05/sitechecker

9c5d99109cfe2cbf46eb9f3cb397fc0f3505f039

[ "MIT" ]

2

2021-02-21T09:24:54.000Z

2021-05-12T18:42:37.000Z

checkerapp/apps.py

sahilr05/sitechecker

9c5d99109cfe2cbf46eb9f3cb397fc0f3505f039

[ "MIT" ]

null

checkerapp/apps.py

sahilr05/sitechecker

9c5d99109cfe2cbf46eb9f3cb397fc0f3505f039

[ "MIT" ]

null

from django.apps import AppConfig class CheckerappConfig(AppConfig): name = "checkerapp"

15.833333

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0.768421

10

95

7.3

0.9

0

0.157895

95

5

35

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0.9125

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1

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false

0

0.333333

0

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null

0

1

0

null

0

1

0

1

0

4

94d3831a6017bc91f6221fb11c2e658d06876a1b

97

py

Python

orientation/apps.py

rahulgrover99/Django-Assignment-JCNU-task

5a610a0b0b1a0eccd438aca08bec2f2e1aee7451

[ "MIT" ]

null

orientation/apps.py

rahulgrover99/Django-Assignment-JCNU-task

5a610a0b0b1a0eccd438aca08bec2f2e1aee7451

[ "MIT" ]

null

orientation/apps.py

rahulgrover99/Django-Assignment-JCNU-task

5a610a0b0b1a0eccd438aca08bec2f2e1aee7451

[ "MIT" ]

null

from django.apps import AppConfig class OrientationConfig(AppConfig): name = 'orientation'

16.166667

35

0.773196

10

97

7.5

0.9

0

0.154639

97

5

36

19.4

0.914634

0

0.113402

0

1

0

false

0

0.333333

0

1

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1

0

null

0

1

0

null

0

1

0

1

0

4

94dc8b8400fb784f93cde3e0cf01c08e61eb1e33

182

py

Python

locationandfeedback/forms.py

singh-sushil/minorproject

02fe8c1dce41109447d5f394bb37e10cb34d9316

[ "MIT" ]

2

2020-12-27T11:28:02.000Z

2021-01-04T07:52:38.000Z

locationandfeedback/forms.py

singh-sushil/minorproject

02fe8c1dce41109447d5f394bb37e10cb34d9316

[ "MIT" ]

1

2020-12-26T13:36:12.000Z

locationandfeedback/forms.py

singh-sushil/minorproject

02fe8c1dce41109447d5f394bb37e10cb34d9316

[ "MIT" ]

null

from django import forms from .models import Feedback class FeedbackForm(forms.ModelForm): class Meta(): model = Feedback fields = ['feedback_text',]

18.2

37

0.642857

19

182

6.105263

0.684211

0

0.274725

182

9

38

20.222222

0.878788

0

0.075145

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1

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false

0

0.333333

0

0.666667

0

1

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null

0

1

0

null

0

1

0

1

0

4

a21c20f617b9a99660f5647bb1d341ef720f3d73

433

py

Python

bradfield/test_x1_02_roman.py

savarin/algorithms

4d1f8f2361de12a02f376883f648697562d177ae

[ "MIT" ]

1

2020-06-16T23:22:54.000Z

bradfield/test_x1_02_roman.py

savarin/algorithms

4d1f8f2361de12a02f376883f648697562d177ae

[ "MIT" ]

null

bradfield/test_x1_02_roman.py

savarin/algorithms

4d1f8f2361de12a02f376883f648697562d177ae

[ "MIT" ]

null

from x1_02_roman import to_roman def test_to_roman(): assert to_roman(1) == "i" assert to_roman(2) == "ii" assert to_roman(3) == "iii" assert to_roman(4) == "iv" assert to_roman(5) == "v" assert to_roman(6) == "vi" assert to_roman(7) == "vii" assert to_roman(8) == "viii" assert to_roman(9) == "ix" assert to_roman(10) == "x" assert to_roman(11) == "xi" assert to_roman(12) == "xii"

25.470588

32

0.586605

71

433

3.338028

0.464789

0.413502

0.658228

0

0.054711

0.240185

433

16

33

27.0625

0.665654

0

0.060046

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0.857143

1

0.071429

true

0

0.071429

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0.142857

0

null

1

0

null

0

1

0

1

0

4

bf41b3184bd3e63550da04859c56c0cfae317902

381

py

Python

Cartwheel/lib/Python26/Lib/site-packages/OpenGL/GL/NV/vertex_program1_1.py

MontyThibault/centre-of-mass-awareness

58778f148e65749e1dfc443043e9fc054ca3ff4d

[ "MIT" ]

null

Cartwheel/lib/Python26/Lib/site-packages/OpenGL/GL/NV/vertex_program1_1.py

MontyThibault/centre-of-mass-awareness

58778f148e65749e1dfc443043e9fc054ca3ff4d

[ "MIT" ]

null

Cartwheel/lib/Python26/Lib/site-packages/OpenGL/GL/NV/vertex_program1_1.py

MontyThibault/centre-of-mass-awareness

58778f148e65749e1dfc443043e9fc054ca3ff4d

[ "MIT" ]

null

'''OpenGL extension NV.vertex_program1_1 This module customises the behaviour of the OpenGL.raw.GL.NV.vertex_program1_1 to provide a more Python-friendly API ''' from OpenGL import platform, constants, constant, arrays from OpenGL import extensions, wrapper from OpenGL.GL import glget import ctypes from OpenGL.raw.GL.NV.vertex_program1_1 import * ### END AUTOGENERATED SECTION

31.75

56

0.813648

58

381

5.241379

0.586207

0.131579

0.157895

0.167763

0.184211

0

0.01791

0.120735

381

12

57

31.75

0.889552

0.48294

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

bf7373cf3f5427580c3173ae34cf4970b206c0c1

689

py

Python

Comentarios.py

SaulPerezP/Proyecto2-IPC1-API

2488c7105fd63d0d8d5b1048a452f613bab4a5b3

[ "Apache-2.0" ]

null

Comentarios.py

SaulPerezP/Proyecto2-IPC1-API

2488c7105fd63d0d8d5b1048a452f613bab4a5b3

[ "Apache-2.0" ]

null

Comentarios.py

SaulPerezP/Proyecto2-IPC1-API

2488c7105fd63d0d8d5b1048a452f613bab4a5b3

[ "Apache-2.0" ]

null

class Comentarios: def __init__(self, videojuego, usuario, comentario): self.videojuego = videojuego self.usuario = usuario self.comentario = comentario #MÉTODOS GET def getVideojuego(self): return self.videojuego def getUsuario(self): return self.usuario def getComentario(self): return self.comentario #MÉTODOS SET def setVideojuego(self, videojuego): self.videojuego = videojuego def setUsuario(self, usuario): self.usuario = usuario def setComentario(self, comentario): self.comentario = comentario #DUMP def dump(self): return { 'videojuego' : self.videojuego, 'usuario': self.usuario, 'comentario': self.comentario }

16.804878

53

0.718433

74

689

6.635135

0.256757

0.171079

0.08554

0

0.187228

689

41

54

16.804878

0.876786

0.037736

0

0.26087

0

0.040909

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0.02439

0

1

0.347826

false

0

0.173913

0.565217

0

null

0

null

0

1

0

1

0

1

0

4

bf80efefe124c8e4d7515de93e5c0cd98539f7a0

247

py

Python

fancy/trainer/training/data_loader_collection.py

susautw/fancy-trainer

eeb7ba1a541a8070171f1be972f8d99f81a4bff9

[ "MIT" ]

null

fancy/trainer/training/data_loader_collection.py

susautw/fancy-trainer

eeb7ba1a541a8070171f1be972f8d99f81a4bff9

[ "MIT" ]

null

fancy/trainer/training/data_loader_collection.py

susautw/fancy-trainer

eeb7ba1a541a8070171f1be972f8d99f81a4bff9

[ "MIT" ]

null

from dataclasses import dataclass from typing import Optional from torch.utils.data import DataLoader @dataclass class DataLoaderCollection: train_loader: DataLoader test_loader: DataLoader valid_loader: Optional[DataLoader] = None

20.583333

45

0.805668

28

247

7

0.607143

0.163265

0

0.153846

247

11

46

22.454545

0.937799

0

1

0

true

0

0.375

0

0.875

0

1

0

null

0

null

0

1

0

1

0

1

0

4

bf8a9f710adffd125e4c29ad2253ff8eb275f128

773

py

Python

backend/accounts/permissions.py

eliefrancois/project2-diabetesapplication-api

e0fd904b1f50eb7ed68fe1ceb74c2a1784e8dc40

[ "MIT" ]

null

backend/accounts/permissions.py

eliefrancois/project2-diabetesapplication-api

e0fd904b1f50eb7ed68fe1ceb74c2a1784e8dc40

[ "MIT" ]

null

backend/accounts/permissions.py

eliefrancois/project2-diabetesapplication-api

e0fd904b1f50eb7ed68fe1ceb74c2a1784e8dc40

[ "MIT" ]

null

from rest_framework import permissions class UpdateOwnProfile(permissions.BasePermission): """Allows patient to edit their own profile""" def has_object_permission(self, request, view, obj): """Validates that patient is trying to edit their own profile""" if request.method in permissions.SAFE_METHODS: return True return obj.id == request.user.id class UpdateOwnReading(permissions.BasePermission): """Allows patient to edit their own readings""" def has_object_permission(self, request, view, obj): """Validates that patient is trying to edit their own reading""" if request.method in permissions.SAFE_METHODS: return True return obj.user_profile.id == request.user.id

35.136364

72

0.69599

95

773

5.578947

0.410526

0.045283

0.083019

0.10566

0.750943

0.724528

0.528302

0

0.225097

773

22

73

35.136364

0.884808

0.258732

0

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0

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false

0

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0

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0

null

0

1

0

null

0

1

0

4

bf8f3e1397150b62a09d3383ecb1db11c3034a33

1,721

py

Python

monstercreator.py

David132639/GUTS2017

fbb06842523713a7998f096f4d785dcc002d6ea5

[ "CC-BY-3.0" ]

1

2018-03-11T21:00:01.000Z

monstercreator.py

David132639/GUTS2017

fbb06842523713a7998f096f4d785dcc002d6ea5

[ "CC-BY-3.0" ]

null

monstercreator.py

David132639/GUTS2017

fbb06842523713a7998f096f4d785dcc002d6ea5

[ "CC-BY-3.0" ]

null

##Gives a list of obstacles given by the case number ##VERSION 1.1 SOHVA fixed a bug with the test case ##Version 1.2 Marija added a boss monster to be in the list by default import monster def createMonsters(case): monsters = [monster.Monster((8,13), [(8, 13), (8, 12), (8, 11), (7,11), (6, 11), (6, 12), (6, 13), (7,13)])] print case if case == 1: monsters += [monster.Monster((3,1),[(3,1),(3,2),(2,2),(2,1)])] monsters += [monster.Monster((7,1),[(7,1),(7,2),(6,2),(6,1)])] monsters += [monster.Monster((7,5),[(7,5),(7,4)])] elif case == 2: monsters += [monster.Monster((2,10),[(2,10),(2,11),(2,12),(3,12),(3,11),(3,10)])] monsters += [monster.Monster((4,8),[(4,8),(5,8),(6,8),(7,8),(8,8),(7,8),(6,8),(5,8)])] route = [] for i in range(1,14): route += [(4,i)] for i in [4,3,2,1]: route += [(i,13)] for i in range(13,0,-1): route += [(1,i)] routeCopy = route + [] for i in reversed(routeCopy[:-1]): route+= [i] monsters += [monster.Monster((4,1),route)] elif case == 3: monsters += [monster.Monster((1,3),[(1,3),(2,3)])] monsters += [monster.Monster((3,1),[(3,1),(3,2),(3,3),(3,2)])] monsters += [monster.Monster((2,8),[(2,8),(2,9),(2,10),(2,11),(2,10),(2,9)])] monsters += [monster.Monster((4,12),[(4,12),(4,12),(4,13),(4,13)])] monsters += [monster.Monster((6,8),[(6,8),(6,9)])] monsters += [monster.Monster((2,1),[(3,1),(4,1),(5,1),(6,1),(7,1),(8,1),(8,1),\ (7,1),(6,1),(5,1),(4,1),(3,1),(2,1),(1,1)])] return monsters

46.513514

113

0.46136

288

1,721

2.756944

0.184028

0.245592

0.360202

0.086902

0.230479

0.079345

0.070529

0

0.157031

0.256246

1,721

36

114

47.805556

0.463281

0.096456

0

null

0

0.032258

null

0.032258

0

null

1

0

1

0

null

0

1

0

4

bf9a42a17d51850e07e6e338c4e02e029f384126

60

py

Python

secrets.py

nainish2/TinderBot

ff7435bcc1974bfe178fb942cda22d7a5933e932

[ "bzip2-1.0.6" ]

null

secrets.py

nainish2/TinderBot

ff7435bcc1974bfe178fb942cda22d7a5933e932

[ "bzip2-1.0.6" ]

null

secrets.py

nainish2/TinderBot

ff7435bcc1974bfe178fb942cda22d7a5933e932

[ "bzip2-1.0.6" ]

null

username= 'aggarwal.nanish@gmail.com' password= 'aggarwal2a'

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bfc2fd685a83c8d4340bbdea5c4527494c3c0c02

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py

Python

python/testData/resolve/multiFile/reimportExported/ReimportExported.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/resolve/multiFile/reimportExported/ReimportExported.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/resolve/multiFile/reimportExported/ReimportExported.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

import mypackage.foo mypackage.bar.dostuff() # <ref>

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bfd717b31b063d444539cc7fed12cd158972bc53

72

py

Python

ch2/2-9.favorite_num.py

AngangGuo/pycrash

de48aa4198022c301f5cd3ce388c195a177be1b5

[ "MIT" ]

null

ch2/2-9.favorite_num.py

AngangGuo/pycrash

de48aa4198022c301f5cd3ce388c195a177be1b5

[ "MIT" ]

null

ch2/2-9.favorite_num.py

AngangGuo/pycrash

de48aa4198022c301f5cd3ce388c195a177be1b5

[ "MIT" ]

null

favorite_number = 23 print(f"My favorite number is {favorite_number}.")

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4

44c6f31866c5683f3f87e1562e15eb8eebd5c75c

8,713

py

Python

test/api/test_radarr.py

shovon668/pycliarr

21ce35e8a63eed8e2bf755a244c66ee3ca9ab278

[ "MIT" ]

10

2020-08-25T08:14:49.000Z

2022-02-27T02:14:19.000Z

test/api/test_radarr.py

shovon668/pycliarr

21ce35e8a63eed8e2bf755a244c66ee3ca9ab278

[ "MIT" ]

27

2020-11-25T05:29:40.000Z

2022-01-22T17:43:42.000Z

test/api/test_radarr.py

shovon668/pycliarr

21ce35e8a63eed8e2bf755a244c66ee3ca9ab278

[ "MIT" ]

1

2021-06-15T16:23:46.000Z

import pytest from copy import deepcopy from unittest.mock import patch from pycliarr.api.radarr import RadarrCli, RadarrMovieItem from pycliarr.api.exceptions import RadarrCliError TEST_ROOT_PATH = [{"path": "some/path/", "id": 1},{"path": "yet/otherpath/", "id": 3}] TEST_JSON = {'somefield': "some value"} TEST_MOVIE = {'title': "some movie", "year": 2020} TEST_HOST = "http://example.com" TEST_APIKEY = "abcd1234" TEST_MOVIEINFO = { "title": "some movie", "sortTitle": "", "sizeOnDisk": 0, "overview": "", "inCinemas": None, "physicalRelease": None, "status": "", "images": [], "website": "", "downloaded": False, "year": 0, "hasFile": False, "youTubeTrailerId": "", "studio": "", "path": "", "rootFolderPath": "", "profileId": 0, "monitored": True, "minimumAvailability": "", "isAvailable": "", "folderName": "", "runtime": 0, "cleanTitle": "", "imdbId": "", "tmdbId": 0, "titleSlug": "", "certification": "", "genres": [], "tags": [], "added": None, "ratings": {}, "collection": {}, "alternativeTitles": [], "qualityProfileId": 0, "id": 0, } @pytest.fixture def cli(): return RadarrCli(TEST_HOST, TEST_APIKEY) @patch("pycliarr.api.radarr.BaseCliMediaApi.get_item", return_value=TEST_MOVIE) def test_get_movie(mock_base, cli): res = cli.get_movie() mock_base.assert_called_with(None) assert res.title == "some movie" assert res.year == 2020 @patch("pycliarr.api.radarr.BaseCliMediaApi.get_item", return_value=[TEST_MOVIE]) def test_get_movie_with_id(mock_base, cli): res = cli.get_movie(movie_id=1234) mock_base.assert_called_with(1234) assert res[0].title == "some movie" assert res[0].year == 2020 @patch("pycliarr.api.radarr.BaseCliMediaApi.lookup_item", return_value=[TEST_MOVIE, TEST_MOVIE]) def test_lookup_movie_with_term(mock_base, cli): res = cli.lookup_movie(term="some title") mock_base.assert_called_with("some title") assert res[0].title == "some movie" assert res[0].year == 2020 @patch("pycliarr.api.radarr.BaseCliMediaApi.lookup_item", return_value=[TEST_MOVIE]) def test_lookup_movie_with_term_single_res(mock_base, cli): res = cli.lookup_movie(term="some title") mock_base.assert_called_with("some title") assert res.title == "some movie" assert res.year == 2020 @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value=TEST_MOVIE) def test_lookup_movie_with_imdb(mock_base, cli): res = cli.lookup_movie(imdb_id="tt1234") mock_base.assert_called_with(f"{cli.api_url_itemlookup}/imdb", url_params={"imdbId": "tt1234"}) assert res.title == "some movie" assert res.year == 2020 @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value=TEST_MOVIE) def test_lookup_movie_with_tmdb(mock_base, cli): res = cli.lookup_movie(tmdb_id=1234) mock_base.assert_called_with(f"{cli.api_url_itemlookup}/tmdb", url_params={"tmdbId": 1234}) assert res.title == "some movie" assert res.year == 2020 @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value=TEST_MOVIE) def test_lookup_movie_with_all(mock_base, cli): res = cli.lookup_movie(term="some title", tmdb_id=1234, imdb_id="tt1234") mock_base.assert_called_with(f"{cli.api_url_itemlookup}/tmdb", url_params={"tmdbId": 1234}) assert res.title == "some movie" assert res.year == 2020 def test_lookup_movie_with_noparam(cli): with pytest.raises(RadarrCliError): cli.lookup_movie() @patch("pycliarr.api.radarr.BaseCliMediaApi.get_root_folder", return_value=TEST_ROOT_PATH) @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value=TEST_MOVIEINFO) @patch("pycliarr.api.radarr.BaseCliMediaApi.add_item", return_value=TEST_JSON) def test_add_movie_withpath(mock_add, mock_root, mock_get, cli): exp = deepcopy(TEST_MOVIEINFO) exp.update({ "title": "some movie", "path": "some/other_path/some_other_movie", "profileId": 1, "qualityProfileId": 1, "monitored": True, "addOptions": {"searchForMovie": True} }) cli.add_movie(quality=1, tmdb_id=1234, path="some/other_path/some_other_movie") mock_add.assert_called_with(json_data=exp) @patch("pycliarr.api.radarr.BaseCliMediaApi.get_root_folder", return_value=TEST_ROOT_PATH) @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value=TEST_MOVIEINFO) @patch("pycliarr.api.radarr.BaseCliMediaApi.add_item", return_value=TEST_JSON) def test_add_movie_withtmdb(mock_add, mock_root, mock_get, cli): exp = deepcopy(TEST_MOVIEINFO) exp.update({ "title": "some movie", "path": "some/path/some movie", "profileId": 1, "qualityProfileId": 1, "monitored": True, "addOptions": {"searchForMovie": True} }) cli.add_movie(quality=1, tmdb_id=1234) mock_add.assert_called_with(json_data=exp) @patch("pycliarr.api.radarr.BaseCliMediaApi.get_root_folder", return_value=TEST_ROOT_PATH) @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value=TEST_MOVIEINFO) @patch("pycliarr.api.radarr.BaseCliMediaApi.add_item", return_value=TEST_JSON) def test_add_movie_withimdb(mock_add, mock_root, mock_get, cli): exp = deepcopy(TEST_MOVIEINFO) exp.update({ "title": "some movie", "path": "some/path/some movie", "profileId": 2, "qualityProfileId": 2, "monitored": True, "addOptions": {"searchForMovie": True} }) cli.add_movie(quality=2, imdb_id="tt1234") mock_add.assert_called_with(json_data=exp) @patch("pycliarr.api.radarr.BaseCliMediaApi.get_root_folder", return_value=TEST_ROOT_PATH) @patch("pycliarr.api.radarr.BaseCliMediaApi.add_item", return_value=TEST_JSON) def test_add_movie_withinfo(mock_add, mock_root, cli): exp = deepcopy(TEST_MOVIEINFO) exp.update({ "title": "some movie", "path": "some/path/some movie", "profileId": 1, "qualityProfileId": 1, "monitored": False, "addOptions": {"searchForMovie": False} }) info = RadarrMovieItem(title="some movie") cli.add_movie(quality=1, movie_info=info, monitored=False, search=False) mock_add.assert_called_with(json_data=exp) @patch("pycliarr.api.radarr.BaseCliMediaApi.request_get", return_value={}) def test_add_movie_noresults(mock_get, cli): with pytest.raises(RadarrCliError): cli.add_movie(quality=2, imdb_id="tt1234") def test_add_movie_noparam(cli): with pytest.raises(RadarrCliError): cli.add_movie(quality=2) @patch("pycliarr.api.radarr.BaseCliMediaApi.delete_item", return_value=TEST_JSON) def test_delete_movie(mock_base, cli): res = cli.delete_movie(1234) mock_base.assert_called_with(1234, True, {}) assert res == TEST_JSON @patch("pycliarr.api.radarr.BaseCliMediaApi.delete_item", return_value=TEST_JSON) def test_delete_movie_withoptions(mock_base, cli): res = cli.delete_movie(1234, delete_files=False, add_exclusion=True) mock_base.assert_called_with(1234, False, {"addExclusion": True}) assert res == TEST_JSON @patch("pycliarr.api.radarr.BaseCliMediaApi._sendCommand", return_value=TEST_JSON) def test_refresh_movies(mock_base, cli): res = cli.refresh_movie() mock_base.assert_called_with({"name": "RefreshMovie"}) assert res == TEST_JSON @patch("pycliarr.api.radarr.BaseCliMediaApi._sendCommand", return_value=TEST_JSON) def test_refresh_movie(mock_base, cli): res = cli.refresh_movie(1234) mock_base.assert_called_with({"name": "RefreshMovie", "movieId": 1234}) assert res == TEST_JSON @patch("pycliarr.api.radarr.BaseCliMediaApi._sendCommand", return_value=TEST_JSON) def test_rescan_movies(mock_base, cli): res = cli.rescan_movie() mock_base.assert_called_with({"name": "RescanMovie"}) assert res == TEST_JSON @patch("pycliarr.api.radarr.BaseCliMediaApi._sendCommand", return_value=TEST_JSON) def test_rescan_movie(mock_base, cli): res = cli.rescan_movie(1234) mock_base.assert_called_with({"name": "RescanMovie", "movieId": 1234}) assert res == TEST_JSON @patch("pycliarr.api.radarr.BaseCliMediaApi.build_item_path") def test_build_movie_path_no_year(mock_buildpath, cli): movie = RadarrMovieItem(title="some movie", year=0) cli.build_movie_path(movie) mock_buildpath.assert_called_with("some movie") @patch("pycliarr.api.radarr.BaseCliMediaApi.build_item_path") def test_build_movie_path_year(mock_buildpath, cli): movie = RadarrMovieItem(title="some movie", year=2020) cli.build_movie_path(movie, root_folder_id=3) mock_buildpath.assert_called_with("some movie (2020)")

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44d2dd32a031c2393f11c750ac9b78bfa9459442

111

py

Python

check/__init__.py

FluvialGeomorph/FluvialGeomorph-toolbox

d7b0712d4841af5cc341443d695bf0481eeccb23

[ "CC0-1.0" ]

null

check/__init__.py

FluvialGeomorph/FluvialGeomorph-toolbox

d7b0712d4841af5cc341443d695bf0481eeccb23

[ "CC0-1.0" ]

1

2021-03-25T12:38:23.000Z

check/__init__.py

FluvialGeomorph/FluvialGeomorph-toolbox

d7b0712d4841af5cc341443d695bf0481eeccb23

[ "CC0-1.0" ]

null

"""The FluvialGeomorph check package contains a set of tools to check the validity of FG feature classes. """

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44f7e10fc7d4a95a36020a0c6c4a3203a5a29693

85

py

Python

examples/Tuning/testing_estimators/nbeats.py

arangatang/Crayon

ff1ca68fe676028a8209ad56c108b8d8179ba2d7

[ "MIT" ]

null

examples/Tuning/testing_estimators/nbeats.py

arangatang/Crayon

ff1ca68fe676028a8209ad56c108b8d8179ba2d7

[ "MIT" ]

null

examples/Tuning/testing_estimators/nbeats.py

arangatang/Crayon

ff1ca68fe676028a8209ad56c108b8d8179ba2d7

[ "MIT" ]

null

from gluonts.model.n_beats import NBEATSEnsembleEstimator NBEATSEnsembleEstimator()

21.25

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null

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null

0

1

0

1

0

4

7803936d5334854af0c64870adcd7f48c61b8602

151

py

Python

virtual/lib/python3.6/site-packages/pylint/test/functional/yield_from_iterable_py33.py

drewheathens/The-Moringa-Tribune

98ee4d63c9df6f1f7497fc6876960a822d914500

[ "MIT" ]

463

2015-01-15T08:17:42.000Z

2022-03-28T15:10:20.000Z

virtual/lib/python3.6/site-packages/pylint/test/functional/yield_from_iterable_py33.py

drewheathens/The-Moringa-Tribune

98ee4d63c9df6f1f7497fc6876960a822d914500

[ "MIT" ]

52

2015-01-06T02:43:59.000Z

2022-03-14T11:15:21.000Z

virtual/lib/python3.6/site-packages/pylint/test/functional/yield_from_iterable_py33.py

drewheathens/The-Moringa-Tribune

98ee4d63c9df6f1f7497fc6876960a822d914500

[ "MIT" ]

249

2015-01-07T22:49:49.000Z

2022-03-18T02:32:06.000Z

""" Check that `yield from`-statement takes an iterable. """ # pylint: disable=missing-docstring def to_ten(): yield from 10 # [not-an-iterable]

18.875

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null

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0

null

0

1

0

4

780ab328d9eee00616536473f2fb2467d5d340e9

61

py

Python

soft_deletion/__init__.py

SocialGouv/ecollecte

1bfce2e0700b563c111c11452356b46ecb2630e4

[ "MIT" ]

9

2018-11-28T07:36:37.000Z

2022-02-04T12:56:11.000Z

soft_deletion/__init__.py

betagouv/e-controle

b6f790ca2590ac257a47930a1e521b86ce3edb29

[ "MIT" ]

154

2018-11-22T14:41:17.000Z

2022-02-12T08:48:57.000Z

soft_deletion/__init__.py

betagouv/e-controle

b6f790ca2590ac257a47930a1e521b86ce3edb29

[ "MIT" ]

10

2018-11-13T06:57:10.000Z

2022-03-21T13:04:49.000Z

default_app_config = 'soft_deletion.apps.SoftDeletionConfig'

30.5

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1

0

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0

1

0

1

null

0

4

785f789dc5d71ff6dbbc2e8cb2cca2ed5b078535

90

py

Python

runserver.py

jasonost/clinicaltrials

b6d003b434e70cf4015215e4c9509df6092cfd97

[ "MIT" ]

12

2015-11-26T22:23:05.000Z

2021-03-23T21:10:53.000Z

runserver.py

jasonost/clinicaltrials

b6d003b434e70cf4015215e4c9509df6092cfd97

[ "MIT" ]

1

2019-01-18T08:33:55.000Z

runserver.py

jasonost/clinicaltrials

b6d003b434e70cf4015215e4c9509df6092cfd97

[ "MIT" ]

4

2015-10-28T05:54:50.000Z

2019-05-09T22:23:11.000Z

from ctapp import app if __name__ == '__main__': app.run(host='0.0.0.0', port=61011)

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null

0

1

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1

0

4

786431e2157ae39d16b9144515372d4a369c12f8

370

py

Python

crawler/crawler/spiders/MyDupeFilter.py

jiady/htdb

70ab10ba8f8031ecd6aa22facaee005d658a387b

[ "MIT" ]

null

crawler/crawler/spiders/MyDupeFilter.py

jiady/htdb

70ab10ba8f8031ecd6aa22facaee005d658a387b

[ "MIT" ]

null

crawler/crawler/spiders/MyDupeFilter.py

jiady/htdb

70ab10ba8f8031ecd6aa22facaee005d658a387b

[ "MIT" ]

null

from scrapy.dupefilters import RFPDupeFilter import redis from crawler import redis_const class MyDupeFilter(RFPDupeFilter): def __init__(self, path=None, debug=False): RFPDupeFilter.__init__(self, path=None, debug=False) self.rclient = redis.StrictRedis(host="localhost", port=6379, db=0) def request_seen(self, request): return False

28.461538

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0

null

0

null

0

1

0

1

0

4

78ac0de8c5e587e65a19d661a4a73d792840ced0

1,746

py

Python

irrexplorer/tests/test_clean_query.py

dashcare/irrexplorer

70977f745769b9d0c761f4d1a92091ec2ae84984

[ "BSD-2-Clause" ]

17

2021-02-12T14:18:16.000Z

2021-08-02T13:20:18.000Z

irrexplorer/tests/test_clean_query.py

dashcare/irrexplorer

70977f745769b9d0c761f4d1a92091ec2ae84984

[ "BSD-2-Clause" ]

76

2021-02-12T13:08:25.000Z

2021-08-19T15:17:14.000Z

irrexplorer/tests/test_clean_query.py

dashcare/irrexplorer

70977f745769b9d0c761f4d1a92091ec2ae84984

[ "BSD-2-Clause" ]

2

2021-06-09T12:44:54.000Z

2021-06-17T14:32:35.000Z

import pytest pytestmark = pytest.mark.asyncio async def test_clean_query_prefix(client): response = await client.get("/api/clean_query/192.0.2/24") assert response.status_code == 200 assert response.json() == {"cleanedValue": "192.0.2.0/24", "category": "prefix"} async def test_clean_query_prefix_misaligned(client): response = await client.get("/api/clean_query/192.0.2.3/24") assert response.status_code == 200 assert response.json() == {"cleanedValue": "192.0.2.0/24", "category": "prefix"} async def test_clean_query_asn_bare(client): response = await client.get("/api/clean_query/192") assert response.status_code == 200 assert response.json() == {"cleanedValue": "AS192", "category": "asn"} async def test_clean_query_asn(client): response = await client.get("/api/clean_query/AS64500") assert response.status_code == 200 assert response.json() == {"cleanedValue": "AS64500", "category": "asn"} async def test_clean_query_as_set(client): response = await client.get("/api/clean_query/foobar") assert response.status_code == 200 assert response.json() == {"cleanedValue": "FOOBAR", "category": "as-set"} async def test_clean_query_invalid(client): response = await client.get("/api/clean_query/--invalid-💩") assert response.status_code == 400 assert "valid prefix" in response.text async def test_clean_query_prefix_too_large(client): response = await client.get("/api/clean_query/192.0.0.0/8") assert response.status_code == 400 assert "the minimum prefix length" in response.text response = await client.get("/api/clean_query/2001::/16") assert response.status_code == 400 assert "the minimum prefix length" in response.text

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0

0.056376

0.146621

1,746

49

85

35.632653

0.750336

0

0.363636

0

0.247995

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0

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0

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0

null

0

1

0

null

0

1

0

4

78b0e8ce1317e231da9dc2ca6bfb101b3156fd6d

89

py

Python

src/files/admin.py

kaleelcsa/Dive-into-AWS-Course---Direct-to-S3-via-Django-JavaScript

b6a5e61288ce745851848eb4853fb70b3e67f1f7

[ "MIT" ]

31

2018-12-17T05:53:01.000Z

2022-01-11T21:54:10.000Z

src/files/admin.py

kaleelcsa/Dive-into-AWS-Course---Direct-to-S3-via-Django-JavaScript

b6a5e61288ce745851848eb4853fb70b3e67f1f7

[ "MIT" ]

5

2020-06-05T19:46:46.000Z

2021-09-08T00:48:21.000Z

src/files/admin.py

codingforentrepreneurs/Dive-into-AWS-Course---Direct-to-S3-via-Django-JavaScript

b6a5e61288ce745851848eb4853fb70b3e67f1f7

[ "MIT" ]

14

2019-01-09T18:33:40.000Z

2022-03-02T20:21:54.000Z

from django.contrib import admin from .models import S3File admin.site.register(S3File)

17.8

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0.820225

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89

5.615385

0.692308

0

0.025316

0.11236

89

5

33

17.8

0.898734

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1

0

true

0

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null

0

1

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null

0

1

0

1

0

4

78bd07a79327d10729adf154c2c302ed30bfefd8

57

py

Python

exercise1-knn/psyc272cava/classifiers/__init__.py

psyc230/cava_exercises

fe7d0107db214e04aa1ed30996373a894e47531f

[ "BSD-2-Clause" ]

1

2019-10-29T01:31:27.000Z

exercise1-knn/psyc272cava/classifiers/__init__.py

psyc230/cava_exercises

fe7d0107db214e04aa1ed30996373a894e47531f

[ "BSD-2-Clause" ]

3

2021-02-02T22:11:28.000Z

2022-01-13T03:03:36.000Z

exercise1-knn/psyc272cava/classifiers/__init__.py

psyc230/cava_exercises

fe7d0107db214e04aa1ed30996373a894e47531f

[ "BSD-2-Clause" ]

2

2019-10-01T00:48:23.000Z

2019-10-22T01:32:46.000Z

from psyc272cava.classifiers.k_nearest_neighbor import *

28.5

56

0.877193

7

57

6.857143

1

0

0.056604

0.070175

57

1

57

0.849057

0

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0

1

0

1

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1

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null

0

1

0

null

0

1

0

1

0

4

78d6ae0d024aa8ec5e5cface12b0dd79f20b82af

65

py

Python

lesson6/theory/matplotlib.py

karina-marques/programming-exercises

ecce7ed3fee02b717bff8e4b8405ea65a574d93b

[ "MIT" ]

null

lesson6/theory/matplotlib.py

karina-marques/programming-exercises

ecce7ed3fee02b717bff8e4b8405ea65a574d93b

[ "MIT" ]

null

lesson6/theory/matplotlib.py

karina-marques/programming-exercises

ecce7ed3fee02b717bff8e4b8405ea65a574d93b

[ "MIT" ]

null

# https://matplotlib.org/stable/tutorials/index.html#introductory

65

0.830769

8

65

6.75

1

0

0.015385

65

1

65

0.84375

0.953846

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

152d40963c407276ecf59d8614f78f4f258d8d9e

314

py

Python

thumt/utils/utils.py

Demon-JieHao/Modeling-Structure-for-Transformer-Network

329831964731ccb7361b847e0ff7c2d809ab7231

[ "BSD-3-Clause" ]

145

2018-12-03T05:47:26.000Z

2022-02-25T07:55:52.000Z

thumt/utils/utils.py

Demon-JieHao/Modeling-Structure-for-Transformer-Network

329831964731ccb7361b847e0ff7c2d809ab7231

[ "BSD-3-Clause" ]

11

2018-12-03T06:03:25.000Z

2021-11-16T12:18:59.000Z

thumt/utils/utils.py

Demon-JieHao/Modeling-Structure-for-Transformer-Network

329831964731ccb7361b847e0ff7c2d809ab7231

[ "BSD-3-Clause" ]

24

2018-12-16T08:42:38.000Z

2021-07-13T04:08:47.000Z

# coding=utf-8 # Copyright 2018 The THUMT Authors from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf def session_run(monitored_session, args): # Call raw TF session directly return monitored_session._tf_sess().run(args)

22.428571

49

0.802548

44

314

5.295455

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0.128755

0.206009

0

0.018727

0.149682

314

13

50

24.153846

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0

1

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false

0

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1

0.166667

0

null

0

1

0

null

0

1

0

4

15401f355aa641a84784a5bf0cf86b597b686b05

107

py

Python

FDApy/clustering/optimalK/__init__.py

vishalbelsare/FDApy

50feb99e34f265b1c17a6f234a9d2f942ceb8f6d

[ "MIT" ]

19

2019-02-11T08:35:29.000Z

2022-01-27T16:51:10.000Z

FDApy/clustering/optimalK/__init__.py

vishalbelsare/FDApy

50feb99e34f265b1c17a6f234a9d2f942ceb8f6d

[ "MIT" ]

4

2020-04-07T07:10:26.000Z

2022-02-09T16:33:19.000Z

FDApy/clustering/optimalK/__init__.py

vishalbelsare/FDApy

50feb99e34f265b1c17a6f234a9d2f942ceb8f6d

[ "MIT" ]

7

2020-04-24T13:24:02.000Z

2022-02-18T17:28:30.000Z

""" OptimalK module. This module is used to determine the best number of clusters in functional data. """

15.285714

74

0.747664

16

107

5

0.9375

0

0.17757

107

6

75

17.833333

0.909091

0.915888

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

15b9d4d595ce224511e4fec52c70f675c385829a

30

py

Python

tests/input_example.py

kangwonlee/reposetman

ca35026a37a9f60479bf19ad542761a56ecd0783

[ "MIT" ]

null

tests/input_example.py

kangwonlee/reposetman

ca35026a37a9f60479bf19ad542761a56ecd0783

[ "MIT" ]

109

2018-09-18T05:50:02.000Z

2020-03-19T04:55:35.000Z

tests/input_example.py

kangwonlee/reposetman

ca35026a37a9f60479bf19ad542761a56ecd0783

[ "MIT" ]

1

2018-09-17T15:39:21.000Z

a = input() b = input('b=?')

7.5

16

0.433333

5

30

2.6

0.6

0.923077

0

0.233333

30

3

17

10

0.565217

0

0.1

0

1

0

false

0

1

0

null

1

0

1

0

null

0

4

15baa7424bf6129d348a094387efb2ad95f3f5b3

636

py

Python

pyaranet4/exceptions.py

stijn-uva/pyaranet4

8d1ed4880db10af2f25ea0e5d4e01461ae695f40

[ "MIT" ]

7

2021-09-14T00:56:26.000Z

2022-01-30T06:08:04.000Z

pyaranet4/exceptions.py

stijn-uva/pyaranet4

8d1ed4880db10af2f25ea0e5d4e01461ae695f40

[ "MIT" ]

null

pyaranet4/exceptions.py

stijn-uva/pyaranet4

8d1ed4880db10af2f25ea0e5d4e01461ae695f40

[ "MIT" ]

1

2021-09-12T20:39:14.000Z

class Aranet4Exception(BaseException): """ Base exception for pyaranet4 """ pass class Aranet4NotFoundException(Aranet4Exception): """ Exception that occurs when no suitable Aranet4 device is available """ pass class Aranet4BusyException(Aranet4Exception): """ Exception that occurs when one attempts to fetch history from the device while history for another sensor is being read """ pass class Aranet4UnpairedException(Aranet4Exception): """ Exception that occurs when the Aranet4 device is detected but unpaired, and no data can be read from it. """ pass

21.931034

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636

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0.060403

0.194631

0.234899

0.261745

0

0.020619

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636

28

80

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0

0.5

0

1

0

true

0.5

0

0.5

0

null

0

1

0

null

0

1

0

4

ec732a4ce7b010b2c9882ee22f31d39cc5b06797

1,184

py

Python

test/Python/Compiler/type_inference.py

marbre/mlir-npcomp

30adf9e6b0c1e94db38050a9e143f20a5a461d17

[ "Apache-2.0" ]

11

2020-03-30T23:31:03.000Z

2021-06-16T01:17:58.000Z

test/Python/Compiler/type_inference.py

marbre/mlir-npcomp

30adf9e6b0c1e94db38050a9e143f20a5a461d17

[ "Apache-2.0" ]

1

2020-04-26T21:19:30.000Z

2020-04-29T18:22:59.000Z

test/Python/Compiler/type_inference.py

marbre/mlir-npcomp

30adf9e6b0c1e94db38050a9e143f20a5a461d17

[ "Apache-2.0" ]

null

# RUN: %PYTHON %s | npcomp-opt -split-input-file -basicpy-type-inference | FileCheck %s --dump-input=fail from npcomp.compiler import test_config import_global = test_config.create_import_dump_decorator() # CHECK-LABEL: func @arithmetic_expression # CHECK-SAME: () -> i64 @import_global def arithmetic_expression(): # CHECK: basicpy.binary_expr{{.*}} : (i64, i64) -> i64 # CHECK: basicpy.binary_expr{{.*}} : (i64, i64) -> i64 # CHECK: basicpy.binary_expr{{.*}} : (i64, i64) -> i64 # CHECK: basicpy.unknown_cast{{.*}} : i64 -> i64 # CHECK: return{{.*}} : i64 return 1 + 2 - 3 * 4 # CHECK-LABEL: func @arg_inference # CHECK-SAME: (%arg0: i64, %arg1: i64) -> i64 @import_global def arg_inference(a, b): # CHECK: basicpy.binary_expr{{.*}} : (i64, i64) -> i64 # CHECK: basicpy.binary_expr{{.*}} : (i64, i64) -> i64 # CHECK: basicpy.unknown_cast{{.*}} : i64 -> i64 # CHECK: return{{.*}} : i64 return a + 2 * b # CHECK-LABEL: func @conditional_inference # CHECK-SAME: (%arg0: i64, %arg1: !basicpy.BoolType, %arg2: i64) -> !basicpy.BoolType @import_global def conditional_inference(cond, a, b): # CHECK-NOT: UnknownType return a if cond + 1 else not (b * 4)

32

105

0.654561

160

1,184

4.70625

0.325

0.103586

0.102258

0.146082

0.413015

0.335989

0

0.066532

0.162162

1,184

36

106

32.888889

0.69254

0.677365

0

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false

0

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0.272727

1

0

null

0

null

0

1

0

1

0

4

ec8974a09e42c122cd04de286650c63acbd53983

544

py

Python

pyspedas/mms/tests/validation/scm.py

MAVENSDC/pyspedas

05ede2603acb514bc7803be054016142c0851685

[ "MIT" ]

1

2020-07-07T19:52:40.000Z

pyspedas/mms/tests/validation/scm.py

MAVENSDC/pyspedas

05ede2603acb514bc7803be054016142c0851685

[ "MIT" ]

null

pyspedas/mms/tests/validation/scm.py

MAVENSDC/pyspedas

05ede2603acb514bc7803be054016142c0851685

[ "MIT" ]

null

from pyspedas import mms_load_scm from pytplot import get_data mms_load_scm() t, d = get_data('mms1_scm_acb_gse_scsrvy_srvy_l2') print(t[0:10].round(6).tolist()) print(d[10000].tolist()) print(d[50000].tolist()) print(d[100000].tolist()) print(d[200000].tolist()) print(d[300000].tolist()) print(d[400000].tolist()) print(d[500000].tolist()) print(d[600000].tolist()) print(d[700000].tolist()) print(d[800000].tolist()) print(d[900000].tolist()) print(d[1000000].tolist()) print(d[1500000].tolist()) print(d[2000000].tolist())

14.702703

50

0.702206

88

544

4.204545

0.420455

0.416216

0.454054

0

0.182365

0.082721

544

36

51

15.111111

0.559118

0

0.056985

0

1

0

true

0

0.105263

0

0.105263

0.789474

0

null

1

0

null

0

1

0

1

0

4

ec998f3461ff848d48a9fd74a474645111e4a732

1,644

py

Python

transformation/functions/tonalfunctions/tonality_permutation_function.py

dpazel/music_rep

2f9de9b98b13df98f1a0a2120b84714725ce527e

[ "MIT" ]

1

2021-05-06T19:45:54.000Z

transformation/functions/tonalfunctions/tonality_permutation_function.py

dpazel/music_rep

2f9de9b98b13df98f1a0a2120b84714725ce527e

[ "MIT" ]

null

transformation/functions/tonalfunctions/tonality_permutation_function.py

dpazel/music_rep

2f9de9b98b13df98f1a0a2120b84714725ce527e

[ "MIT" ]

null

""" File: tonality_permutation_function.py Purpose: Class defining a function based on a permutation of a tonality's tones. """ from transformation.functions.tonalfunctions.tonal_function import TonalFunction from transformation.functions.tonalfunctions.tonality_permutation import TonalityPermutation class TonalityPermutationFunction(TonalFunction): """ Class implementation of a function based on a tonality permutation. """ def __init__(self, tonality_permutation, extension_map=None): """ Concstructor using a tonality permutation. :param domain_tonality: :param tonality_permutation: TonalityPermutation. :param extension_map: Note: the permutation_cycles is strictly used for initialization. During usage, settings and deletes may change the mapping of the given tonality's tones. """ self._tonality_permutation = tonality_permutation domain_tonality = tonality_permutation.tonality primary_map = tonality_permutation.map TonalFunction.__init__(self, domain_tonality, domain_tonality, primary_map, extension_map) @staticmethod def create(tonality, cycles, extension_map = None): """ Construction using a tonality and cycles. :param tonality: :param cycles: :param extension_map: :return: """ return TonalityPermutationFunction(TonalityPermutation(tonality, cycles), extension_map) @property def tonality_permutation(self): return self._tonality_permutation def __str__(self): return str(self.tonality_permutation)

32.88

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1,644

6.88024

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0.08007

0.02785

0.029591

0

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113

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0

null

1

0

null

0

1

0

1

0

4

eca90320bde86d20e960c7c410d4d58f9955ed61

23

py

Python

src/iris/__init__.py

minhaz1/iris

6f251a915e77d7882db13d7900ae37324b077520

[ "BSD-2-Clause" ]

null

src/iris/__init__.py

minhaz1/iris

6f251a915e77d7882db13d7900ae37324b077520

[ "BSD-2-Clause" ]

null

src/iris/__init__.py

minhaz1/iris

6f251a915e77d7882db13d7900ae37324b077520

[ "BSD-2-Clause" ]

null

__version__ = "1.0.36"

11.5

22

0.652174

4

23

2.75

1

0

0.2

0.130435

23

1

23

0.35

0

0.26087

0

1

0

false

0

1

0

null

0

1

0

1

0

null

0

4

01b774ac8cbffe9b27293fc638eb7e268f29e750

132

py

Python

app/resources/hello_world.py

daveflr/Flask-Restful-Template

2e6c5de0347bf82ccd3a4244202eee79d263d762

[ "MIT" ]

null

app/resources/hello_world.py

daveflr/Flask-Restful-Template

2e6c5de0347bf82ccd3a4244202eee79d263d762

[ "MIT" ]

null

app/resources/hello_world.py

daveflr/Flask-Restful-Template

2e6c5de0347bf82ccd3a4244202eee79d263d762

[ "MIT" ]

null

from flask_restful import Resource class HelloWorld(Resource): @staticmethod def get(): return {"hello": "world"}

16.5

34

0.666667

14

132

6.214286

0.928571

0

0.227273

132

7

35

18.857143

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0

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0

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true

0

0.2

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

4

bf1ef78ba4d3ce8d11e09c4693724f3af8f59630

23

py

Python

examples/py27-0026-set-literals2.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

8

2020-11-21T22:39:41.000Z

2022-03-13T18:45:53.000Z

examples/py27-0026-set-literals2.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

1

2021-12-10T10:45:38.000Z

examples/py27-0026-set-literals2.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

1

2022-02-07T11:16:38.000Z

{i for i in range(3)}

7.666667

21

0.565217

6

23

2.166667

0.833333

0

0.058824

0.26087

23

2

22

11.5

0.705882

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

4

171142041890920f4a9b87780fb50ce13766b470

237

py

Python

tests/test_nsct.py

njarvis/nsct

acad19818ab097363e6fba1c1e75bf47c6a41381

[ "MIT" ]

4

2018-02-26T04:46:09.000Z

2018-09-06T06:28:51.000Z

tests/test_nsct.py

njarvis/nsct

acad19818ab097363e6fba1c1e75bf47c6a41381

[ "MIT" ]

null

tests/test_nsct.py

njarvis/nsct

acad19818ab097363e6fba1c1e75bf47c6a41381

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ test_nsct ---------------------------------- Tests for `nsct` module. """ class TestNsct(object): @classmethod def set_up(self): pass @classmethod def tear_down(self): pass

13.166667

34

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24

237

4.666667

0.791667

0.25

0

0.005618

0.248945

237

17

35

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0.623596

0.392405

0

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0

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false

0.285714

0

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0

1

0

null

1

0

null

0

1

0

1

0

4

172e74efb205df7a3151a47e62e7fd3fd367fe10

1,307

bzl

Python

third_party/com_fasterxml_jackson_module.bzl

wix/exodus

dfb0c9713b07a8b6a49b548b7b543021e748d80b

[ "MIT" ]

186

2019-06-05T01:02:53.000Z

2022-03-31T10:44:19.000Z

third_party/com_fasterxml_jackson_module.bzl

wix/exodus

dfb0c9713b07a8b6a49b548b7b543021e748d80b

[ "MIT" ]

25

2019-06-04T23:18:55.000Z

2021-09-22T03:44:25.000Z

third_party/com_fasterxml_jackson_module.bzl

wix/exodus

dfb0c9713b07a8b6a49b548b7b543021e748d80b

[ "MIT" ]

17

2019-06-04T18:45:19.000Z

2022-01-20T09:40:04.000Z

load("//:import_external.bzl", import_external = "safe_wix_scala_maven_import_external") def dependencies(): import_external( name = "com_fasterxml_jackson_module_jackson_module_paranamer", artifact = "com.fasterxml.jackson.module:jackson-module-paranamer:2.9.6", artifact_sha256 = "dfd66598c0094d9a7ef0b6e6bb3140031fc833f6cf2e415da27bc9357cdfe63b", srcjar_sha256 = "375052d977a4647b49a8512a2e269f3296c455544f080a94bc8855dbfd24ad75", deps = [ "@com_fasterxml_jackson_core_jackson_databind", "@com_thoughtworks_paranamer_paranamer" ], ) import_external( name = "com_fasterxml_jackson_module_jackson_module_scala_2_12", artifact = "com.fasterxml.jackson.module:jackson-module-scala_2.12:2.9.6", artifact_sha256 = "c775854c1da6fc4602d5850b65513d18cb9d955b3c0f64551dd58ccb24a85aba", srcjar_sha256 = "5446419113a48ceb4fa802cd785edfc06531ab32763d2a2f7906293d1e445957", deps = [ "@com_fasterxml_jackson_core_jackson_annotations", "@com_fasterxml_jackson_core_jackson_core", "@com_fasterxml_jackson_core_jackson_databind", "@com_fasterxml_jackson_module_jackson_module_paranamer", "@org_scala_lang_scala_library", "@org_scala_lang_scala_reflect" ], )

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119

1,307

7.731092

0.302521

0.141304

0.18587

0.13587

0.506522

0.436957

0.395652

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0

0.175663

0.163734

1,307

30

92

43.566667

0.666057

0

0.307692

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0.038462

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1

0.038462

true

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null

0

1

0

1

null

0

1

0

4

173db5f145cdf33a6c0d4b3a0a022a091270db97

222

py

Python

proxy_overrides/related.py

datamade/django-proxy-overrides

d8ad7e7ba33507a77ee17444cb1da7a630e2b479

[ "BSD-3-Clause" ]

7

2018-12-13T13:12:31.000Z

2021-06-15T14:34:36.000Z

proxy_overrides/related.py

datamade/django-proxy-overrides

d8ad7e7ba33507a77ee17444cb1da7a630e2b479

[ "BSD-3-Clause" ]

5

2018-11-27T21:13:48.000Z

2020-05-15T12:24:49.000Z

proxy_overrides/related.py

datamade/django-proxy-overrides

d8ad7e7ba33507a77ee17444cb1da7a630e2b479

[ "BSD-3-Clause" ]

4

2018-11-30T16:21:20.000Z

2019-09-17T23:03:51.000Z

from django.db.models import ForeignKey from .base import ProxyField class ProxyForeignKey(ProxyField): def __init__(self, *args, **kwargs): super(ProxyForeignKey, self).__init__(ForeignKey(*args, **kwargs))

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222

6.28

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0.13964

222

7

75

31.714286

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null

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1

0

null

0

1

0

1

0

4

173eb525ddbe7b3e57a2d6eb7b7a4aa5434fe599

225

py

Python

rangeesh/star_wars/admin.py

Rangeeshar/Django-Project

7f229c726a22228a335c6e993e3852f16c5552b1

[ "MIT" ]

null

rangeesh/star_wars/admin.py

Rangeeshar/Django-Project

7f229c726a22228a335c6e993e3852f16c5552b1

[ "MIT" ]

null

rangeesh/star_wars/admin.py

Rangeeshar/Django-Project

7f229c726a22228a335c6e993e3852f16c5552b1

[ "MIT" ]

null

from django.contrib import admin from star_wars.models import People, Species @admin.register(People) class PeopleAdmin(admin.ModelAdmin): pass @admin.register(Species) class SpeciesAdmin(admin.ModelAdmin): pass

16.071429

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0.782222

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225

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0.148571

0.217143

0

0.133333

225

13

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0.25

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true

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1

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null

0

1

0

null

0

1

0

4

17586891f27f087e90f361d842150e56ba710561

158

py

Python

jrnl/__main__.py

TonyRoomZ/jrnl

75459bb9fcd19107d56b9560094137924e88959f

[ "MIT" ]

null

jrnl/__main__.py

TonyRoomZ/jrnl

75459bb9fcd19107d56b9560094137924e88959f

[ "MIT" ]

null

jrnl/__main__.py

TonyRoomZ/jrnl

75459bb9fcd19107d56b9560094137924e88959f

[ "MIT" ]

null

#!/usr/bin/env python # encoding: utf-8 from __future__ import absolute_import, unicode_literals from . import cli if __name__ == "__main__": cli.run()

17.555556

56

0.727848

22

158

4.590909

0.818182

0

0.007519

0.158228

158

8

57

19.75

0.75188

0.227848

0

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true

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0.5

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0.5

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null

0

1

0

null

0

1

0

1

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4

1761fceb95910d0d663d2148909d3b1ac01da55d

284

py

Python

src/data_generator/day_ahead_extractors/pse/real_basic_data.py

BlooAM/Day-ahead-prices

e5c51682de4bb2b093fd6412b2131012e7e836ca

[ "MIT" ]

null

src/data_generator/day_ahead_extractors/pse/real_basic_data.py

BlooAM/Day-ahead-prices

e5c51682de4bb2b093fd6412b2131012e7e836ca

[ "MIT" ]

null

src/data_generator/day_ahead_extractors/pse/real_basic_data.py

BlooAM/Day-ahead-prices

e5c51682de4bb2b093fd6412b2131012e7e836ca

[ "MIT" ]

null

from src.data_generator.day_ahead_extractors.pse.base_day_ahead_extractor import PseDataDayAheadExtractor __all__ = ('RealBasicDataDayAheadExtractor',) class RealBasicDataDayAheadExtractor(PseDataDayAheadExtractor): def _get_prediction_flag(self) -> bool: return False

31.555556

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27

284

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0

0.105634

284

8

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0

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1

0

null

0

1

0

null

0

1

0

4

1771546d9586b3e008225b64eba03c9691a016f2

28,053

py

Python

configuration/alexa_responses.py

gruporofex/alexa_rofex

338eb1e08da37a45f44eaab70a633e255d4b2be7

[ "Apache-2.0" ]

null

configuration/alexa_responses.py

gruporofex/alexa_rofex

338eb1e08da37a45f44eaab70a633e255d4b2be7

[ "Apache-2.0" ]

null

configuration/alexa_responses.py

gruporofex/alexa_rofex

338eb1e08da37a45f44eaab70a633e255d4b2be7

[ "Apache-2.0" ]

1

2019-06-02T14:17:14.000Z

# -*- coding: utf-8 -*- """ Alexa responses for the english version """ import config as conf INIT_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Welcome to ROFEX Skill", 'card_output': "Please, tell me an instrument and I'll give you the last price " "available for the contract. " "If you need help asking me questions just say 'HELP'", 'speech_output': "<speak>Welcome to ROFEX Skill. " "<s>Please, tell me an instrument and I'll give you the last price " "available for the contract.</s> " "<s>If you need help just say 'HELP'</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Bienvenido al Skill de ROFEX", 'card_output': "Por favor, dime un instrumento y te diré el último precio disponible para ese contrato. " "Si necesitas ayuda solo dí la palabra 'AYUDA'", 'speech_output': "<speak>Bienvenido al Skill de ROFEX. " "<s>Por favor, dime un instrumento y te diré el último precio disponible para ese contrato.</s> " "<s>Si necesitas ayuda solo dí 'AYUDA'.</s></speak>", 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } DEFAULT_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Default Response", 'card_output': "Sorry, I didn't get that. Please repeat it.", 'speech_output': "Sorry, I didn't get that. Please repeat it.", 'reprompt_text': "Could you repeat it please?", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Respuesta Genérica", 'card_output': "Perdón, no entendí lo que dijiste. ¿Podrías repetirlo por favor?", 'speech_output': "Perdón, no entendí lo que dijiste. ¿Podrías repetirlo por favor?", 'reprompt_text': "¿Podrías repetirlo por favor?", 'should_end_session': False } } ASK_INSTRUMENT_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Tell me the Instrument", 'card_output': "Please, tell me the instrument you want to know.", 'speech_output': "<speak>Please, tell me the instrument you want to know.</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'.", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Hasta luego", 'card_output': "Por favor, dime el instrumento que desas saber.", 'speech_output': "<speak>Por favor, dime el instrumento que deseas saber.</speak>", 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } END_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Bye Bye", 'card_output': "Thank you! Have a nice day.", 'speech_output': "Thank you! Have a nice day.", 'reprompt_text': "", 'should_end_session': True }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Hasta luego", 'card_output': "Gracias! Que tengas un lindo día.", 'speech_output': "Gracias! Que tengas un lindo día.", 'reprompt_text': "", 'should_end_session': True } } LANGUAGE_NOT_SUPPORTED = { 'session_attributes': {}, 'card_title': "Language Not Supported", 'card_output': "Sorry, I do not recognize this language: {0}.", 'speech_output': "<speak>Sorry, I don't recognize this language: {0}.</speak>", 'reprompt_text': "", 'should_end_session': True } ERROR_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "An Error Occurred", 'card_output': "Sorry, I couldn't process your request. Please, try again.", 'speech_output': "<speak><s>Sorry, an error has occurred and I couldn't process your request.</s> " "Please, ask me again.</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Ocurrió un Error", 'card_output': "Lo siento, no pude procesar tu consulta. Por favor, inténtalo de nuevo.", 'speech_output': "<speak><s>Lo siento, ocurrió un error y no pude procesar tu consulta.</s> " "Por favor, inténtalo de nuevo.</speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } LAST_PRICE_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "ROFEX Price", 'card_output': "", 'speech_output': "", 'reprompt_text': "", 'should_end_session': False }, conf.Language.ES: { 'session_attributes': {}, 'card_title': "Precios ROFEX", 'card_output': "", 'speech_output': "", 'reprompt_text': "", 'should_end_session': False } } LAST_PRICE_OK_RESPONSE = { conf.Language.EN : { 'card_output': "The price for {0} future {1} contract is {2}. " "Can I help you with another instrument?", 'speech_output': '<speak><s>The price for {0} future {1} contract is {2}.</s> ' '<break time="1s"/>Can I help you with another instrument?</speak>', 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "El precio para el futuro de {0} posición {1} es {2}. " "¿Puedo ayudarte con otro instrumento?", 'speech_output': '<speak><s>El precio para el futuro de {0} posición {1} es {2}.</s> ' '<break time="1s"/>¿Puedo ayudarte con otro instrumento?</speak>', 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'." } } LAST_PRICE_OK_RESPONSE_SPOT = { conf.Language.EN : { 'card_output': "Last price for {0} is {1}. " "Can I help you with another instrument?", 'speech_output': "<speak><s>Last price for {0} is {1}.</s> " "<break time='1s'/>Can I help you with another instrument?</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "El último precio para el {0} es {1}. " "¿Quieres consultarme otro instrumento?", 'speech_output': "<speak><s>El último precio para el {0} es {1}.</s> " "<break time='1s'/>¿Quieres consultarme otro instrumento?</speak>", 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'." } } ENTRY_PRICE_OK_RESPONSE = { conf.Language.EN : { 'card_output': "{0} for {1} future {2} contract is {3}. Want to try it again?", 'speech_output': "<speak><s>{0} for {1} future {2} contract is {3}.</s> " "<break time='1s'/>Can I help you with another instrument?</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "El {0} para el futuro de {1} posición {2} es {3}. " "¿Quieres consultarme otro instrumento?", 'speech_output': "<speak><s>El {0} para el futuro de {1} posición {2} es {3}.</s> " "<break time='1s'/>¿Quieres consultarme otro instrumento?</speak>", 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'." } } LAST_PRICE_ERROR_RESPONSE = { conf.Language.EN : { 'card_output': "Sorry, this is not a valid instrument. Please ask me again.", 'speech_output': "<speak><s>Sorry, this is not a valid instrument.</s> Please, try with another instrument.</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "Perdón, ese no es un instrumento válido. Por favor, intenta con otro instrumento.", 'speech_output': "<speak><s>Perdón, ese no es un instrumento válido.</s> Por favor, intenta con otro instrumento.</speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'." } } LAST_PRICE_INSTRUMENT_NOT_FOUND_RESPONSE = { conf.Language.EN : { 'card_output': "I could not find a valid instrument for {0} future {1} contract. " "The most recent position for this instrument is {2}. " "Please try again with this position.", 'speech_output': "<speak><s>I could not find a valid instrument for {0} future {1} contract.</s> " "<s>The most recent position for this instrument is {2}</s>. " "<s>Please try again with this position.</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "El futuro de {0} no posee una posición abierta para el mes de {1}. " "La posición más reciente para este instrumento es {2}. " "Por favor, intenta de vuelta con dicha posición.", 'speech_output': "<speak><s>El futuro de {0} no posee una posición abierta para el mes de {1}.</s> " "<s>La posición más reciente para este instrumento es {2}.</s> " "<s>Por favor, intenta de vuelta con dicha posición.</s></speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'." } } LAST_PRICE_MD_NOT_FOUND_RESPONSE = { conf.Language.EN : { 'card_output': "Sorry, there are no data available for {0} future {1} contract. " "Please, try again with another instrument.", 'speech_output': "<speak>Sorry, there are no data available for {0} future {1} contract. " "Please, try again with another instrument.</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "Perdón, en estos momentos no hay datos disponible para el futuro de {0} posición {1}. " "¿Quieres consultarme otro instrumento?", 'speech_output': "<speak><s>Perdón, no hay datos disponible para este futuro todavía.</s> " "¿Quieres consultarme otro instrumento?</speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'." } } ENTRY_PRICE_MD_NOT_FOUND_RESPONSE = { conf.Language.EN : { 'card_output': "Sorry, {0} is not available for this instrument now. " "Please, try again with another data or instrument.", 'speech_output': "<speak><s>Sorry, {0} is not available for this instrument now.</s> " "<s>Please, try again with another data or instrument.</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'" }, conf.Language.ES: { 'card_output': "Perdón, en este momento no hay {0} disponible para este instrumento. " "Por favor, intentalo de nuevo con otro dato o instrumento.", 'speech_output': "<speak><s>Perdón, en este momento no hay {0} disponible para este instrumento.</s> " "<s>Por favor, intentalo de nuevo con otro dato o instrumento.</s></speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'." } } ############################################################################################### ############################################################################################### # 1 - Help Possibilities HELP_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Help!", 'card_output': "If you want to know how to ask the price of an instrument, " "say 'Question' and I'll help you. " "Also, I can tell you the list of valid instruments, just say 'Instruments', " "and to know the list of available data of an " "instruments, say 'Instruments Data'. Want to try it?", 'speech_output': "<speak>If you want to know how to ask the price of an instrument, say " "<s><prosody volume='x-loud'>'Question'</prosody></s> " "and I'll help you. Also, I can tell you the list of valid instruments, just say " "<s><prosody volume='x-loud'>'Instruments'</prosody></s>, " "and to know the list of available data of an instrument, say " "<s><prosody volume='x-loud'>'Instruments Data'</prosody></s>. " "<break time='1s'/>Want to try it?</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "AYUDA!", 'card_output': "Si quieres saber como preguntarme el precio de un instrumento, " "dime 'Preguntar' y te ayudaré. " "También te puedo decir la lista de instrumentos válidos, " "solo dí 'Instrumentos', " "y para conocer la lista de datos disponibles sobre " "un instrumento, dí 'Datos Instrumentos'. " "¿Quieres intentarlo?", 'speech_output': "<speak>Si quieres saber como preguntarme el precio de un instrumento, dime " "<s><prosody volume='x-loud'>'Preguntar'</prosody></s>" " y te ayudaré. También te puedo decir la lista de instrumentos válidos, solo dí " "<s><prosody volume='x-loud'>'Instrumentos'</prosody></s>" ", y para conocer la lista de datos disponibles sobre un instrumento, dí " "<s><prosody volume='x-loud'>'Datos Instrumentos'</prosody></s>. " "<break time='1s'/>¿Quieres intentarlo?</speak>", 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } # 1.1 - Question Response QUESTION_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "How to ask me?", 'card_output': "To know the price of an instrument just tell me " "the instrument's name and, optionally, " "the month of the contract. Additionally, " "you could specify the market data you want to know. " "Want to try it?", 'speech_output': "<speak><s>To know the price of an instrument just tell me " "the instrument's name and, optionally, " "the month of the contract.</s> <s>Additionally, " "you could specify the market data you want to know.</s> " "<break time='1s'/>Want to try it?</speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Como preguntar?", 'card_output': "Para saber el precio de un instrumento solo tienes que " "decirme el nombre del instrumento y, opcionalmente, " "el mes del contrato. Adicionalmente, puedes especificar " "el dato de mercado que deseas saber. " "¿Quieres intentarlo?", 'speech_output': "<speak><s>Para saber el precio de un instrumento solo tienes que " "decirme el nombre del instrumento y, opcionalmente, " "el mes del contrato.</s> <s>Adicionalmente, puedes especificar " "el dato de mercado que deseas saber.</s> " "<break time='1s'/>¿Quieres intentarlo?</speak>", 'reprompt_text': "Si deseas terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } # 1.2 - Instruments List Response INSTRUMENT_LIST_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Instruments List", 'card_output': "You can ask me for the following instruments: " "Dollar: for dollar futures. " "ROFEX Index: for ROFEX 20 Index futures. " "Gold: for gold futures. " "Oil: for oil futures. " "Soybean: for soybean futures. " "Corn: for corn futures. " "Wheat: for wheat futures. " "If you want more details about any instrument " "just say 'Help' and the name of the instrument. " "Want to try it?", 'speech_output': "<speak><s>You can ask me for the following instruments:</s> " "<s><prosody volume='x-loud'>Dollar</prosody>: for dollar futures.</s> " "<s><prosody volume='x-loud'>ROFEX Index</prosody>: for ROFEX 20 Index futures.</s> " "<s><prosody volume='x-loud'>Gold</prosody>: for gold futures.</s> " "<s><prosody volume='x-loud'>Oil</prosody>: for oil futures.</s> " "<s><prosody volume='x-loud'>Soybean</prosody>: for soybean futures.</s> " "<s><prosody volume='x-loud'>Corn</prosody>: for corn futures.</s> " "<s><prosody volume='x-loud'>Wheat</prosody>: for wheat futures.</s> " "<s>If you want more details about any instrument " "just say <s><prosody volume='x-loud'>'Help'</prosody></s> and the name of the instrument.</s> " "<break time='1s'/><s>Want to try it?</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Lista Instrumentos", 'card_output': "Puedes consultarme los siguientes instrumentos: " "Dólar: para futuros de dólar. " "Índice ROFEX: para futuros sobre el Índice ROFEX 20. " "Oro: para futuros de oro. " "Petróleo: para futuros de petróleo. " "Soja: para futuros de soja. " "Maíz: para futuros de maíz. " "Trigo: para futuros de trigo. " "Si quieres saber más detalles acerca de algún instrumento " "solo dí 'Ayuda' y el nombre del instrumento. " "¿Quieres intentarlo?", 'speech_output': "<speak>Puedes consultarme los siguientes instrumentos: " "<s><prosody volume='x-loud'>Dólar</prosody>: para futuros de dólar.</s> " "<s><prosody volume='x-loud'>Índice ROFEX</prosody>: para futuros sobre el Índice ROFEX 20.</s> " "<s><prosody volume='x-loud'>Oro</prosody>: para futuros de oro.</s> " "<s><prosody volume='x-loud'>Petróleo</prosody>: para futuros de petróleo.</s> " "<s><prosody volume='x-loud'>Soja</prosody>: para futuros de soja.</s> " "<s><prosody volume='x-loud'>Maíz</prosody>: para futuros de maíz.</s> " "<s><prosody volume='x-loud'>Trigo</prosody>: para futuros de trigo.</s> " "<s>Si quieres saber más detalles acerca de algún instrumento " "solo dí <prosody volume='x-loud'>'Ayuda'</prosody> y el nombre del instrumento.</s> " "<break time='1s'/><s>¿Quieres intentarlo?</s></speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } # 1.2.1 - Instruments Detailed Response HELP_RELATED_INST_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Instrument Detail", 'card_output': "Ok, when you mention the instrument '{0}', I will tell you " "the last price available for the contract. " "Also, let me tell you that there are other {0} " "related instruments, like: {1}. " "Just tell me the instrument full name and I will tell you the price. " "Want to try it?", 'speech_output': "<speak><s>Ok, when you mention the instrument <prosody volume='x-loud'>'{0}'</prosody>, " "I will tell you the last price available for the contract.</s> " "<s>Also, let me tell you that there are other {0} " "related instruments, like:</s> {1}. " "<s>Just tell me the instrument full name and I will tell you the price.</s> " "<break time='1s'/><s>Want to try it?</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Detalle Instrumento", 'card_output': "Bien, cuando menciones el instrumento '{0}' te diré el " "último percio disponible para ese contrato. " "También puedes consultar otros instrumentos relacionados con {0} como: {1}. " "Solo dí el nombre del instrumento completo y te diré el precio. " "¿Quieres intentarlo?", 'speech_output': "<speak><s>Bien, cuando menciones el instrumento <prosody volume='x-loud'>'{0}'</prosody> " "te diré el último percio disponible para ese contrato.</s> " "<s>También puedes consultar otros instrumentos relacionados con {0} como:</s> {1}. " "<s>Solo dí el nombre del instrumento completo y te diré el precio.</s> " "<break time='1s'/><s>¿Quieres intentarlo?</s></speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } # 1.2.2 - Instruments Detailed Response Default HELP_INSTRUMENT_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Instrument Detail", 'card_output': "Ok, when you mention the instrument '{0}', I will tell you " "the last price available for the contract. For example, to know the " "price of {0} future June contract, just say '{0} June'. " "Want to try it?", 'speech_output': "<speak><s>Ok, when you mention the instrument <prosody volume='x-loud'>'{0}'</prosody>, " "I will tell you the last price available for the contract.</s> <s>For example, to know the " "price of {0} future June contract, just say <prosody volume='x-loud'>'{0} June'</prosody>.</s> " "<break time='1s'/><s>Want to try it?</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Detalle Instrumento", 'card_output': "Bien, cuando menciones el instrumento '{0}' te diré el " "último percio disponible para ese contrato. Por ejemplo, para saber " "el precio del futuro sobre {0} posición Junio, " "solo tienes que decir '{0} Junio'. ¿Quieres intentarlo?", 'speech_output': "<speak><s>Bien, cuando menciones el instrumento <prosody volume='x-loud'>'{0}'</prosody>" " te diré el último percio disponible para ese contrato.</s> <s>Por ejemplo, para saber " "el precio del futuro sobre {0} posición Junio, solo tienes que decir " "<prosody volume='x-loud'>'{0} Junio'</prosody>.</s>" "<break time='1s'/><s>¿Quieres intentarlo?</s></speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } } # 1.3 - Market Data List ENTRY_LIST_RESPONSE = { conf.Language.EN : { 'session_attributes': {}, 'card_title': "Market Data List", 'card_output': "When asking for an instrument you could also " "specify the market data you want to know about. " "Now, the available data are: " "Last Price, Settlement Price, Effective Volume, " "Nominal Volume and Open Interest. " "Want to try it?", 'speech_output': "<speak><s>When asking for an instrument you could also " "specify the market data you want to know about.</s> " "<s>Now, the available data are:</s> " "<prosody volume='x-loud'>Last Price</prosody>, " "<prosody volume='x-loud'>Settlement Price</prosody>, " "<prosody volume='x-loud'>Effective Volume</prosody>, " "<prosody volume='x-loud'>Nominal Volume</prosody> and " "<prosody volume='x-loud'>Open Interest</prosody>. " "<break time='1s'/><s>Want to try it?</s></speak>", 'reprompt_text': "If you want to end the conversation just say 'Goodbye'", 'should_end_session': False }, conf.Language.ES : { 'session_attributes': {}, 'card_title': "Lista Datos de Mercado", 'card_output': "Al consultar un instrumento también puedes especificar " "el dato de mercado que deseas saber. " "Por ahora, los datos disponibles son: " "Último Precio, Precio de Ajuste, Volumen Efectivo, " "Volumen Nominal e Interés Abierto. " "¿Quieres intentarlo?", 'speech_output': "<speak><s>Al consultar un instrumento también puedes especificar " "el dato de mercado que deseas saber.</s> " "<s>Por ahora, los datos disponibles son:</s> " "<prosody volume='x-loud'>Último Precio</prosody>, " "<prosody volume='x-loud'>Precio de Ajuste</prosody>, " "<prosody volume='x-loud'>Volumen Efectivo</prosody>, " "<prosody volume='x-loud'>Volumen Nominal</prosody> e " "<prosody volume='x-loud'>Interés Abierto</prosody>. " "<break time='1s'/><s>¿Quieres intentarlo?</s></speak>", 'reprompt_text': "Si quieres terminar la conversación solo dí 'Adiós Alexa'.", 'should_end_session': False } }

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0.841916

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null

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null

0

4

178fc4bc5799fef4d49a269da036bef10307919b

217

py

Python

math/average.py

parmalatinter/ai

2bf7ae17013e8ae48d62b4c2892ee3a1d0a21648

[ "MIT" ]

null

math/average.py

parmalatinter/ai

2bf7ae17013e8ae48d62b4c2892ee3a1d0a21648

[ "MIT" ]

7

2021-03-25T23:01:51.000Z

2022-03-12T00:26:49.000Z

math/average.py

parmalatinter/ai

2bf7ae17013e8ae48d62b4c2892ee3a1d0a21648

[ "MIT" ]

null

#!/usr/bin/env python # 平均の求め方 def Average(numList): return sum(numList) / len(numList) def main(): numList = [1, 2, 3] print(Average(numList)) if __name__ == "__main__": main()

12.764706

39

0.562212

26

217

4.384615

0.692308

0.245614

0

0.019355

0.285714

217

16

40

13.5625

0.716129

0.124424

0

0.046512

0

1

0.285714

false

0

0.142857

0.428571

0.142857

1

0

null

1

0

null

0

1

0

1

0

4